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@incollection{castellano2007recognising,
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@inproceedings{chenMSC2012,
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@inproceedings{demirdjianICMI2009,
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@inproceedings{patronBMVC2010,
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@inproceedings{deep3,
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@inproceedings{andriluka2009pictorial,
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@article{neuro,
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    TITLE = "Multi-modal Gesture Recognition Challenge 2013:
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    BOOKTITLE = "ChaLearn Multi-Modal Gesture Recognition Grand Challenge and Workshop, 15th ACM International Conference on Multimodal Interaction",
    YEAR = {2013}   }


@article{escalera2013multi2,
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@article{citizen,
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@article{[FWG09],
  title =      {Visual Human-Machine Learning},
  author =     {R. Fuchs and J.  Waser and M. E. Gr{\"o}ller},
  year =       {2009},
  pages =      {1327--1334},
  month =      oct,
  number =     {6},
  issn =       {1077-2626},
  journal =    {IEEE TVCG},
  volume =     {15}
}

@article{ref1,
author = { V. Garcia and E. Debreuve and M. Barlaud },
title = { Fast k nearest neighbor search using GPU },
booktitle = { In Proceedings of the CVPR Workshop on Computer Vision on GPU },
year = {2008},
location = { Anchorage, Alaska, USA },
}

@InProceedings{ref2,
author = { O. Maitre and L. A. Baumes and N. Lachiche and A. Corma and P. Collet },
title = { Coarse grain parallelization of evolutionary alhorithms on GPGPU cards with EASEA },
booktitle = { In Proceedings of the 11th Annual conference on Genetic and evolutionary computation },
year = {2009},
pages = {1403--1410},
location = {Canada},
}

@InProceedings{ref3,
author = {B. Catanzaro and N. Sundaram and K. Keutzer},
title = { Fast support vector machine training and classification on graphics processors },
booktitle = { Proceedings of the 25th international conference on Machine learning },
year = {2008},
pages = {104--111},
}

@InProceedings{ref4,
author = { D. Yang and L Getao and D. Jenkins and G. Peterson and H. Li },
title = { High Performance Relevance Vector Machine on GPUs },
booktitle = { Symposium on Application Accelerators in High Performance Computing },
year = {2010},
}

@InProceedings{ref5,
author = { L. Zhang and R. Nevatia },
title = { Efficient scan-window based object detection using GPGPU },
booktitle = { Computer Vision and Pattern Recognition },
year = {2008},
}

@InProceedings{ref6,
author = { D. Yudanov and M. Shaaban and R. Melton and L. Reznik },
title = {GPU-Based Simulation of Spiking Neural Networks with Real-Time Performance and High Accuracy },
booktitle = {WCCI-2010, Special Session Computational Intelligence on Consumer Games and Graphics Hardware CIGPU-2010},
year = {2010},
}

@InProceedings{ref7,
author = {S. Herrero and J. Williams and A. Sanchez },
title = { Parallel Multiclass Classification using SVMs on GPUs },
booktitle = { ACM International Conference Proceeding Series, Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units },
volume = {425},
year = {2010},
pages = {2--11},
location = { Pittsburgh, Pennsylvania },
}

@InProceedings{ref8,
author = {H. Ghorayeb and B. Steux and C. Laurgeau},
title = {Boosted Algorithms for Visual Object Detection on Graphics Processing Units},
booktitle = {Computer Vision ACCV 2006},
pages = {254--263},
volume = {3852},
year = {2006},
}


@article{validation,
author={J. Demsar},
title={Statistical Comparisons of Classifiers over Multiple Data Sets},
journal={JMLR},
volume={7},
pages={1-30},
year={2006}
}


@Article{[VKG05],
  author =        {I. Viola and A. Kanitsar and M. E. Gr\"oller},
  title =        {Importance-driven feature enhancement in volume
                 visualization},
  journal =      {IEEE Trans. on Visualization and Computer
                 Graphics},
  year =         {2005},
  volume =       {11},
  number =       {4},
  pages =        {408--418},
  annote =         {Degrees of interest, Importance function, sparness
                 function, two-level rendering}
 }

@Article{[KSW06],
  author =       {J. Kr\"uger and J. Schneider and R. Westermann},
  title =        {ClearView: An Interactive Context Preserving Hotspot
                 Visualization Technique},
  year =         {2006},
  month =        {sep- oct},
  journal =      {IEEE Trans. on Visualization and Computer
                 Graphics (Proc. Visualization / Information
                 Visualization 2006)},
  volume =       {12},
  number =       {5},
  annote =       {Focus+context}
 }

@inproceedings {[BHW07],
  author = {M. Burns and M. Haidacher and W. Wein and I. Viola and E. Groeller},
  title = {Feature Emphasis and Contextual Cutaways for Multimodal Medical
    Visualization},
  booktitle = {Eurographics / IEEE VGTC Symposium on Visualization 2007},
  year = 2007,
  month = may,
  pages = {275--282},
  annote = {focus + context, FT importance function, cutaways}
}

@techreport{[KBK08],
  title =      {The LiveSync Interaction Metaphor for Smart User-Intended
               Visualization},
  author =     {P. Kohlmann and S. Bruckner and A. Kanitsar and
               M.E. Gr{\"o}ller},
  year =       2008,
  address =    {Favoritenstrasse 9-11/186, A-1040 Vienna, Austria},
  institution = {Institute of Computer Graphics and Algorithms, Vienna
               University of Technology},
  month =      jan,
  number =     {TR-186-2-08-01},
  URL =        {http://www.cg.tuwien.ac.at/research/publications/2008/TR-186-2-08-01/},
  annote =     {Interficie, focus+context}
}


@article{[Dui00],
author = {Anil K. Jain and Robert P.W. Duin and Jianchang Mao},
title = {Statistical Pattern Recognition: A Review},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {22},
issn = {0162-8828},
year = {2000},
pages = {4-37},
doi = {http://doi.ieeecomputersociety.org/10.1109/34.824819},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA}
}

@article{grapp11,
author = {Oscar Amoros and Sergio Escalera and Anna Puig},
title = {Adaboost GPU-based Classifier for Direct Volume Rendering},
journal ={International Conference on Computer Graphics Theory and Applications},
year = {2011},
pages = {215-219}
}


@InProceedings{focus,
   author =       {P. Abellan and A. Puig and D. Tost},
   title =        {Focus+context rendering of structured biomedical data},
   booktitle = {EG VCBM 2008 : Eurographics workshop on visual computing
for biomedicine},
   pages =     {109-116},
   year =      {2008}
}

@inproceedings{GPU-stencil,
  author = {P. Micikevicius},
  title = {3D finite difference computation on GPUs using CUDA},
  booktitle = {Workshop on General Purpose Processing
on Graphics Processing Units},
  year = {2009},
  pages = {79-84}
}

@journal{tilera,
    author =    {S. Bell and B. Edwards and J. Amann},
 title = {{TILE64 Processor: A 64-Core SoC with Mesh Interconnect}},
   pages = {88-598},
   journal = {Solid-State Circuits Conference, 2008},
   doi = {10.1109/ISSCC.2008.4523070},
   url = {http://dx.doi.org/10.1109/ISSCC.2008.4523070},
   year = {2008}
}

@MISC{amoros,
  author =       {O. Amoros},
  title =        {{SimpleOpenCL Library}},
  howpublished = {Website},
  year =         {2011},
  note =         {http://code.google.com/p/simple-opencl/}
}

@techreport{DelaTorreHMV08,
   author    = {Fernando {De la Torre} and Jessica K. Hodgins and Javier Montano and Sergio Valcarcel},
   title     = {Detailed Human Data Acquisition of Kitchen Activities: the {CMU}-Multimodal Activity Database ({CMU-MMAC})},
   institution = {RI-TR-08-22h, CMU},
   year        = {2008}
}

@InProceedings{Ferrari08,
  author       = "Ferrari, V. and Marin-Jimenez, M. and Zisserman, A.",
  title        = "Progressive Search Space Reduction for Human Pose Estimation",
  booktitle    = "CVPR",
  year         = "2008",
}

@inproceedings{Johnson10,
   title = {Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation},
   author = {Johnson, S. and Everingham, M.},
   year = {2010},
   booktitle = {BMVC},
   note = {doi:10.5244/C.24.12}
}

@inproceedings{laptev2008learning,
  title={Learning realistic human actions from movies},
  author={Laptev, I. and Marszalek, M. and Schmid, C. and Rozenfeld, B.},
  booktitle={CVPR},
  pages={1--8},
  year={2008}
}

@inproceedings{gcd,
   author =    {{Apple Inc.}},
   title =    {Grand Central Dispatch (GCD) Reference},
   url ={https://developer.apple.com/library/mac/#documentation/Performance/Reference/GCD_libdispatch_Ref/Reference/reference.html}
}

@inproceedings{nvidia,
   title = {OpenCL Programming for CUDA architecture 2009},
   url   = {http://www.nvidia.com/content/cudazone/download/OpenCL/NVIDIA_OpenCL_ProgrammingOverview.pdf}
}


@inproceedings{latency,
   author =      {Sean Baxter},
   title =    {Modern GPU 2011},
   url ={http://www.moderngpu.com/intro/performance.html}
}


@inproceedings{PacificGraphics,
  author = {S. Escalera and A. Puig and O. Amoros and M. Salamo},
  title = {Intelligent GPGPU Classification in Volume Visualization: a framework based on Error-Correcting Output Codes},
  booktitle = {Pacific Graphics},
  year = {2011}
}


@inproceedings{opencl,
  author = {SIGGRAPH},
  title = {OpenCL},
  booktitle = {SIGGRAPH2009},
  year = {2008}
}

@book{giffard2012adapteva,
  title={Adapteva},
  author={Giffard, P.V.},
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  url={http://books.google.es/books?id=pms9LgEACAAJ},
  year={2012},
  publisher={Betascript Publishing}
}

@inProceedings{DPurl,
    author = {Purl},
    title = {Dynamic Parallelism in CUDA},
    journal = {NVidia developers},
    year = {2012},
    url = {http://developer.download.nvidia.com/assets/cuda/files/CUDADownloads/TechBrief_Dynamic_Parallelism_in_CUDA.pdf}
}
@ARTICLE{mpi,
    author = {E. Lusk and N. Doss and A. Skjellum},
    title = {A high-performance, portable implementation of the MPI
message passing interface standard},
    journal = {Parallel Computing},
    year = {1996},
    volume = {22},
    pages = {789--828}
}


@MISC{FPGA,
  author =       {{Altera Corporation}},
  title =        {{Implementing FPGA Design with the OpenCL Standard}},
  howpublished = {Website},
  year =         {2011},
  note =         {http://www.altera.com/literature/wp/wp-01173-opencl.pdf}
}
@MISC{EpiphanyHardware,
  author =       {{Adapteva Inc.}},
  title =        {{Epiphany Architecture Reference}},
  howpublished = {Website},
  year =         {2012},
  note =         {http://www.adapteva.com/wp-content/uploads/2012/10/epiphany\_arch\_reference\_3.12.10.03.pdf}
}
@MISC{EpiphanySoftware,
  author =       {{Adapteva Inc.}},
  title =        {{Epiphany SDK Reference}},
  howpublished = {Website},
  year =         {2012},
  note =         {http://www.adapteva.com/wp-content/uploads/2012/10/epiphany\_sdk\_reference\_3.12.10.03.pdf}
}
@MISC{CUDADynamicParallelism,
  author =       {{NVIDIA Corporation}},
  title =        {{Dynamic Parallelism in CUDA}},
  howpublished = {Website},
  year =         {2012},
  note =         {http://developer.download.nvidia.com/assets/cuda/files/CUDADownloads/TechBrief\_Dynamic\_Parallelism\_in\_CUDA.pdf}
}


@book{Kirk:2010:PMP:1841511,
 author = {Kirk, David B. and Hwu, Wen-mei W.},
 title = {Programming Massively Parallel Processors: A Hands-on Approach},
 year = {2010},
 isbn = {0123814723, 9780123814722},
 edition = {1st},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
}

@article{boykov2006graph,
  title={Graph cuts and efficient ND image segmentation},
  author={Boykov, Yuri and Funka-Lea, Gareth},
  journal={International Journal of Computer Vision},
  volume={70},
  number={2},
  pages={109--131},
  year={2006},
  publisher={Springer}
}

@article{boykov2001fast,
  title={Fast approximate energy minimization via graph cuts},
  author={Boykov, Yuri and Veksler, Olga and Zabih, Ramin},
  journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
  volume={23},
  number={11},
  pages={1222--1239},
  year={2001},
  publisher={IEEE}
}

@misc{Authors14,
 author = {Authors},
 title = {The frobnicatable foo filter},
 note = {BMVC14 submission ID 324. Supplied as additional material {\tt bmvc14.pdf}},
 year = 2014
}

@misc{Authors14b,
 author = {Authors},
 title = {Frobnication tutorial},
 note = {Supplied as additional material {\tt tr.pdf}},
 year = 2014
}

@article{Alpher02,
author = {A. Alpher},
title = {Frobnication},
journal = {Journal of Foo},
volume = 12,
number = 1,
pages = {234--778},
year = 2002
}

@article{Alpher03,
author = {A. Alpher and and J.~P.~N. Fotheringham-Smythe},
title = {Frobnication revisited},
journal = {Journal of Foo},
volume = 13,
number = 1,
pages = {234--778},
year = 2003
}

@article{Alpher04,
author = {A. Alpher and and J.~P.~N. Fotheringham-Smythe and G. Gamow},
title = {Can a machine frobnicate?},
journal = {Journal of Foo},
volume = 14,
number = 1,
pages = {234--778},
year = 2004
}


% Journals
@STRING{SMC = {IEEE Transactions on Systems, Man and Cybernetics}}
@STRING{CVIU = {Computer Vision and Image Understanding}}
@STRING{IJCV = {International Journal of Computer Vision}}
@STRING{IVC = {Image and Vision Computing}}
@STRING{PR = {Pattern Recognition}}
@STRING{PRL = {Pattern Recognition Letters}}
@STRING{PAMI = {IEEE Transactions on Pattern Analysis and Machine Intelligence}}

% Conferences
@STRING{ASSP = {IEEE International Conference on Acoustics, Speech and Signal   Processing}}
@STRING{ACCV = {Asian Conference on Computer Vision}}
@STRING{MVA = {IAPR Conference on Machine Vision Applications}}
@STRING{BMVC = {BMVA British Machine Vision Conference}}
@STRING{CVPR = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition}}
@STRING{ECCV = {European Conference on Computer Vision}}
@STRING{FGR = {IEEE International Conference on Automatic Face and Gesture Recognition}}
@STRING{GW = {International Gesture Workshop}}
@STRING{IbCPRIA = {Iberian Conference on Pattern Recognition and Image Analysis}}
@STRING{ICCV = {IEEE International Conference on Computer Vision}}
@STRING{ICDM = {IEEE International Conference on Data Mining}}
@STRING{ICPR = {IAPR International Conference on Pattern Recognition}}
@STRING{LREC = {Language Resources and Evaluation Conference}}
@STRING{ICIP = {IEEE International Conference on Image Processing}}

%Associations
@STRING{EMBS = {IEEE Engineering in Medicine and Biology Society}}

%Misc
@STRING{LNCS = {Lecture Notes in Computer Science}}
@STRING{PROCS = {Proceedings of the }}
@STRING{WKSHP = {Workshop : }}
@STRING{INT = {International }}
@STRING{CONF = {Conference }}


@IEEETRANBSTCTL{IEEEexample:BSTcontrol,
  CTLdash_repeated_names = {no},
  CTLname_url_prefix = {URL : }
}


@BOOK{BritishDeafAssociation_Dictionary_1992,
  title = {Dictionary of British Sign Language/English},
  publisher = {Faber and Faber},
  year = {1992},
  author = {{British Deaf Association} }
}

@MANUAL{Hanke_Sign_2004,
  title = {Sign Language Notation System},
  author = {Hanke, T and Schmaling, C},
  organization = {Institute of German Sign Language and Communication of the Deaf},
  address = {Hamburg, Germany},
  month = jan,
  year = {2004},
  url = {http://www.sign-lang.uni-hamburg.de/projects/hamnosys.html}
}

@INPROCEEDINGS{Kim_Adaptation_1993,
  author = {Kim, S and Waldron, M.B},
  title = {Adaptation of Self Organizing Network for {ASL} Recognition},
  booktitle = PROCS # { Annual International Conference of the IEEE Engineering
    in Engineering in Medicine and Biology Society},
  year = {1993},
  pages = {254 -- 254},
  address = {San Diego, California, USA},
  month = oct # { 28 -- 31},
  abstract = {Modified labeling process for Kohonen’s Self Organizing

    Network was developed to explore the expandability of

    American Sign Language (ASL) vocabulary recognition. The

    labeling process was developed for handshape recognition and

    then applied to recognize ASL words. The advantage of this

    method is that the network does not have to be retrained to

    increase the learned set only re labeled thus making the

    \earning more adaptable},
  file = {:Kim_Adaptation_1993.pdf:PDF},
  keywords = {SON},
  review = {Data Gloves

    Concentrates soley on 36 handshapes

    Notes the phonemic level of sign.

    13 signs up to 16 signs later.

    can't find the previous paper.

    1 page paper!}
}




@ARTICLE{gesturefirst1,
  author = {D. McNeil},
  title = {How Language Began, Gesture and Speech in Human Evolution},
  journal = {Cambridge editorial},
  year = {2012}}

@ARTICLE{gesturefirst2,
  author = {G. Hewes},
  title = {Primate communication and the gestural origins of language},
  journal = {Current Antropology},
  year = {1973},
  volume = {14},
  pages = {5-24}}




@ARTICLE{Stokoe_Sign_1960,
  author = {Stokoe, W.C},
  title = {Sign Language Structure: An Outline of the Visual Communication Systems
    of the American Deaf},
  journal = {Studies in Linguistics: Occasional Papers},
  year = {1960},
  volume = {8},
  pages = {3 -- 37},
  abstract = {It is approaching a half century since Bill Stokoe published

    his revolutionary monograph, Sign Language Structure: An

    Outline of the Visual Communication Systems of the American

    Deaf. It is rare for a work of innovative scholarship to spark

    a social as well as an intellectual revolution, but that is just

    what Stokoe’s 1960 paper did. And it is indicative both of

    Stokoe’s genius and of his commitment that he did not

    simply publish his groundbreaking work and then sit back to

    watch the revolutions unfold. He actively promoted

    important changes in at least three areas of social and

    intellectual life. First, and perhaps most important, his work,

    that was ultimately generally accepted as showing the signing

    of deaf people to be linguistic, supported significant changes

    in the way deaf children are educated around the globe.

    Second, his work led to a general rethinking of what is

    fundamental about human language; and, third, it helped to

    reenergize the moribund field of language origin studies.

    This truly revolutionary paper has been reprinted at least

    twice, in revised and original versions, since its initial release

    in 1960, and now, five years after Bill’s death, it is good to see

    it once again brought before the general public},
  file = {:Stokoe_Sign_1960.pdf:PDF},
  owner = {Helen},
  timestamp = {2009.10.27}
}

@INPROCEEDINGS{Waldron_Parsing_1989,
  author = {Waldron, M.B. and Simon, D},
  title = {Parsing method for signed telecommunication},
  booktitle = PROCS # { Annual International Conference of the IEEE Engineering
    in Engineering in Medicine and Biology Society: Images of the Twenty-First
    Century},
  year = {1989},
  volume = {6},
  pages = {1798 -- 1799},
  address = {Seattle, Washington, USA},
  month = nov,
  abstract = {A technique for parsing and coding sign language is presented. The
    code can be used to generate and send signs over the telephone lines.
    A system called the graphics communication device (GCD), which can
    transmit the constructed signs in full duplex over regular telephone
    lines, has been developed for use by deaf persons. In the initial
    coding, the most often used hand shape, position, orientation, and
    movement of the hands are supported. As a result, some of the signs
    may not have the proper representation. Since the sign subcomponents
    are organized hierarchically in a tree structure a more extensive
    set of signs can be easily included. The method of parsing and coding
    of the signs is described in detail},
  doi = {10.1109/IEMBS.1989.96461},
  file = {:Waldron_Parsing_1989.pdf:PDF},
  keywords = {data communication systems, encoding, handicapped aids, languagesdeaf
    persons, graphics communication device, hand movement, hand orientation,
    hand position, hand shape, parsing method, regular telephone lines,
    sign language, sign subcomponents, signed telecommunication, tree
    structure}
}

@ARTICLE{Waldron_Isolated_1995,
  author = {Waldron, M. B. and Kim, S},
  title = {Isolated {ASL} sign recognition system for deaf persons},
  journal = {IEEE Transactions on Rehabilitation Engineering},
  year = {1995},
  volume = {3},
  pages = {261 -- 271},
  number = {3},
  month = sep,
  abstract = {Abstract-In this paper, the design and evaluation of a two-

    stage neural network which can recognize isolated ASL signs is

    given. The input to this network is the hand shape and position

    data obtained from a DataGlove mounted with a Polhemus

    sensor. The first level consists of four backpropagation neural


    networks which can recognize the sign language phonology,

    namely, the 36 hand shapes, 10 locations, 11 orientations, and


    11 hand movements. The recognized phonemes from the begin-

    ning, middle, and end of the sign are fed to the second stage


    which recognizes the actual signs. Both backpropagation and

    Kohonen’s self-organizing neural work was used to compare the

    performance and the expandability of the learned vocabulary.

    In the current work, six signers with Mering hand sizes signed

    14 signs which included hand shape, position, and motion fragile

    and triple robust signs. When a backpropagation network was

    used for the second stage, the results show that the network was

    able to recognize these signs with an overall accuracy of 86%.


    Further, the recognition results were linearly dependent on the

    size of the finger to the metacarpohalangeal (MP) joint and the

    total length of the hand. When the second stage was a Kohonen’s

    self-organizing network, the network could not only recognize the


    signs with 84\% accuracy, but also expand its learned vocabulary


    through relabeling},
  doi = {10.1109/86.413199},
  file = {Waldron_Isolated_1995.pdf:Waldron_Isolated_1995.pdf:PDF},
  keywords = {SON},
  owner = {Helen},
  review = {NN and Data Gloves

    14 Words

    Phoneme level},
  timestamp = {2009.10.25}
}

@INPROCEEDINGS{Waldron_Increasing_1994,
  author = {Waldron, M. B. and Kim, S},
  title = {Increasing manual sign recognition vocabulary through relabelling},
  booktitle = PROCS # { IEEE International Conference on Neural Networks IEEE World
    Congress on Computational Intelligence},
  year = {1994},
  volume = {5},
  pages = {2885 -- 2889},
  address = {Orlando, Florida, USA},
  month = jun # { 27 -- } # jul # { 2},
  abstract = {In this paper we present the results of relabelling a self organizing
    map (SOM) to increase the dynamic manual signs it can recognize.
    Relabelling exploits the global ordering of self organizing map and
    abrogates the need for retraining, thereby reducing the computational
    costs and increasing the recognition ability of the network. This
    relabelling technique was applied to a dynamic sign recognition system
    to increase the recognition vocabulary from 10 to 14 signs. The data
    was collected from a person wearing a DataGlove with a Polhemus sensor
    and signing the 14 signs. The sampled hand data over the duration
    of sign was fed to phonemic recognition modules and the collective
    outputs of these modules were fed to the sign recognition module
    consisting of a relabelled self organizing network. The results showed
    that the overall recognition rate of the relabelled network was 84\%
    as compared to 86\% for the retrained network. Further, it was found
    that the dynamic sampling of the signs made the movement phoneme
    module unnecessary},
  doi = {10.1109/ICNN.1994.374689},
  file = {:Waldron_Increasing_1994.pdf:PDF},
  keywords = {SON},
  owner = {Helen},
  timestamp = {2009.10.25}
}

@INPROCEEDINGS{Vogler_Adapting_1997,
  author = {Vogler, C. and Metaxas, D},
  title = {Adapting hidden Markov models for {ASL} recognition by using three-dimensional
    computer vision methods},
  booktitle = PROCS # { IEEE International Conference on Systems, Man, and Cybernetics},
  year = {1997},
  volume = {1},
  pages = {156 -- 161},
  address = {Orlando, FL, USA},
  month = oct # { 12 -- 15},
  abstract = {We present an approach to continuous American sign language (ASL)
    recognition, which uses as input 3D data of arm motions. We use computer
    vision methods for 3D object shape and motion parameter extraction
    and an ascension technologies `Flock of Birds' interchangeably to
    obtain accurate 3D movement parameters of ASL sentences, selected
    from a 53-sign vocabulary and a widely varied sentence structure.
    These parameters are used as features for hidden Markov models (HMMs).
    To address coarticulation effects and improve our recognition results,
    we experimented with two different approaches. The first consists
    of training context-dependent HMMs and is inspired by speech recognition
    systems. The second consists of modeling transient movements between
    signs and is inspired by the characteristics of ASL phonology. Our
    experiments verified that the second approach yields better recognition
    results},
  file = {:Vogler_Adapting_1997.pdf:PDF},
  keywords = {sign-language-recognition hidden-markov-models 3d continuous-sign},
  pdf = {Vogler_Adapting_1997.pdf},
  review = {Uses similar HMMs to previous work but takes the unusual step of modeling
    the co-articulation (epenthesis) explicitly to aid in recognition.

    Uses data gloves to be real time but has a visual version too},
  timestamp = {2009.10.24}
}

@ARTICLE{Liddell_American_1989,
  author = {Liddell, S.K. and Johnson, R.E},
  title = {American Sign Language: The Phonological Base},
  journal = {Sign Language Studies},
  year = {1989},
  volume = {64},
  pages = {195 -- 278},
  abstract = {Outlines phonological structure and processes of American Sign Language
    (ASL), covering: (1) sequential phenomena found in the production
    of individual signs; (2) the segmental phonetic transcription system;
    (3) paradigmatic and syntagmatic contrasts in ASL signs; (4) similarities
    between ASL and spoken language phonological processes; and (5) phonological
    effects on morphological processes. (20 references) (Author/CB)},
  owner = {Helen},
  timestamp = {2009.10.27}
}

@INPROCEEDINGS{Kadir_Minimal_2004,
  author = {Kadir, T. and Bowden, R. and Ong, E.J. and Zisserman, A},
  title = {Minimal training, large lexicon, unconstrained sign language recognition},
  volume = {2},
  pages = {939 -- 948},
  abstract = {This paper presents a flexible monocular system capable of recognising
    sign lexicons far greater in number than previous approaches. The
    power of the system is due to four key elements: (i) Head and hand
    detection based upon boosting which removes the need for temperamental
    colour segmentation; (ii) A body centred description of activity
    which overcomes issues with camera placement, calibration and user;
    (iii) A two stage classification in which stage I generates a high
    level linguistic description of activity which naturally generalises
    and hence reduces training; (iv) A stage II classifier bank which
    does not require HMMs, further reducing training requirements. The
    outcome of which is a system capable of running in real-time, and
    generating extremely high recognition rates for large lexicons with
    as little as a single training instance per sign. We demonstrate
    classification rates as high as 92\% for a lexicon of 164 words with
    extremely low training requirements outperforming previous approaches
    where thousands of training examples are required},
  crossref = {BMVC04},
  file = {:Kadir_Minimal_2004.pdf:PDF},
  keywords = {sign-language-recognition},
  pdf = {Kadir_Minimal_2004.pdf},
  timestamp = {2009.10.24}
}



@INPROCEEDINGS{Yin_Learning_2009,
  author = {Yin, P. and Starner, T. and Hamilton, H. and Essa, I. and Rehg,
    J.M.},
  title = {Learning the basic units in American Sign Language using discriminative
    segmental feature selection},
  booktitle = PROCS # ASSP,
  year = {2009},
  pages = {4757 -- 4760},
  address = {Taipei, Taiwan},
  month = apr # { 19 -- 24},
  abstract = {The natural language for most deaf signers in the United States is
    American Sign Language (ASL). ASL has internal structure like spoken
    languages, and ASL linguists have introduced several phonemic models.
    The study of ASL phonemes is not only interesting to linguists, but
    also useful for scalability in recognition by machines. Since machine
    perception is different than human perception, this paper learns
    the basic units for ASL directly from data. Comparing with previous
    studies, our approach computes a set of data-driven units (fenemes)
    discriminatively from the results of segmental feature selection.
    The learning iterates the following two steps: first apply discriminative
    feature selection segmentally to the signs, and then tie the most
    similar temporal segments to re-train. Intuitively, the sign parts
    indistinguishable to machines are merged to form basic units, which
    we call ASL fenemes. Experiments on publicly available ASL recognition
    data show that the extracted data-driven fenemes are meaningful,
    and recognition using those fenemes achieves improved accuracy at
    reduced model complexity},
  doi = {10.1109/ICASSP.2009.4960694},
  file = {Yin_Learning_2009.pdf:Yin_Learning_2009.pdf:PDF},
  issn = {1520-6149},
  keywords = {natural language interfaces, natural languages, American sign language,
    discriminative segmental feature selection, machine perception, natural
    language, phonemic model, reduced model complexity, American Sign
    Language, Feature Selection, Machine Learning},
  owner = {Helen},
  timestamp = {2009.10.27}
}


@INPROCEEDINGS{Kong_Automatic_2008,
  author = {Kong, W.W. and Ranganath, S.},
  title = {Automatic hand trajectory segmentation and phoneme transcription
    for sign language},
  pages = {1 -- 6},
  abstract = {This paper presents an automatic approach to segment

    3-D hand trajectories and transcribe phonemes based on

    them, as a step towards recognizing American sign language

    (ASL).We first apply a segmentation algorithm which

    detects minimal velocity and maximal change of directional

    angle to segment the hand motion trajectory of naturally

    signed sentences. This yields oversegmented trajectories,

    which are further processed by a trained na¨?ve Bayesian detector

    to identify true segmented points and eliminate false

    alarms. The above segmentation algorithm yielded 88.5%

    true segmented points and 11.8% false alarms on unseen

    ASL sentence samples. These segmentation results were refined

    by a simple majority voting scheme, and the final segments

    obtained were used to transcribe phonemes for ASL.

    This was based on clustering PCA-based features extracted

    from training sentences. We then trained Hidden Markov

    Models (HMMs) to recognize the sequence of phonemes in

    the sentences. On the 25 test sentences containing 157 segments,

    the average number of errors obtained was 15.6.},
  crossref = {FG08},
  doi = {10.1109/AFGR.2008.4813462},
  file = {:Kong_Automatic_2008.pdf:PDF},
  owner = {Helen},
  timestamp = {2009.10.24}
}



@ARTICLE{Han_Modelling_2009,
  author = {Han, J.W. and Awad, G. and Sutherland, A.},
  title = {Modelling and segmenting subunits for sign language recognition based
    on hand motion analysis},
  journal = PRL,
  year = {2009},
  volume = {30},
  pages = {623 -- 633},
  number = {6},
  month = apr,
  abstract = {Modelling and segmenting subunits is one of the important topics in
    sign language study. Many scholars have proposed the functional definition
    to subunits from the view of linguistics while the problem of efficiently
    implementing it using computer vision techniques is a challenge.
    On the other hand, a number of subunit segmentation work has been
    investigated for the task of vision-based sign language recognition
    whereas their subunits either somewhat lack the linguistic support
    or are improper. In this paper, we attempt to define and segment
    subunits using computer vision techniques, which also can be basically
    explained by sign language linguistics. A subunit is firstly defined
    as one continuous visual hand action in time and space, which comprises
    a series of interrelated consecutive frames. Then, a simple but efficient
    solution is developed to detect the subunit boundary using hand motion
    discontinuity. Finally, temporal clustering by dynamic time warping
    is adopted to merge similar segments and refine the results. The
    presented work does not need prior knowledge of the types of signs
    or number of subunits and is more robust to signer behaviour variation.
    Furthermore, it correlates highly with the definition of syllables
    in sign language while sharing characteristics of syllables in spoken
    languages. A set of comprehensive experiments on real-world signing
    videos demonstrates the effectiveness of the proposed model},
  bibsource = {http://www.visionbib.com/bibliography/people932.html#TT88474},
  file = {:Han_Modelling_2009.pdf:PDF},
  pdf = {Han_Modelling_2009.pdf},
  timestamp = {2009.10.24}
}

@INPROCEEDINGS{Cooper_Sign_2010a,
  author = {Cooper, H. and Bowden, R.},
  title = {Sign Language Recognition using Linguistically Derived Sub-Units},
  booktitle = PROCS # LREC # {Workshop on the Representation and Processing of Sign
    Languages : Corpora and Sign Languages Technologies},
  year = {2010},
  address = {Valetta, Malta},
  month = may # {17 -- 23},
  owner = {Helen},
  timestamp = {2010.05.14}
}

@INPROCEEDINGS{Pitsikalis_Advances_2011,
  author = {Pitsikalis, V. and Theodorakis, S. and Vogler, C. and Maragos, P.},
  title = {Advances in Phonetics-based Sub-Unit Modeling for Transcription Alignment
    and Sign Language Recognition},
  booktitle = PROCS # INT # CONF # CVPR # WKSHP # {Gesture Recognition},
  crossref = {CVPR11}
}

@INPROCEEDINGS{Ershaed_Arabic_2011,
  author = {Ershaed, H. and Al-Alali, I. and Khasawneh, N. and Fraiwan, M.},
  title = {An Arabic Sign Language Computer Interface Using the Xbox Kinect},
  booktitle = {Annual Undergraduate Research Conf. on Applied Computing},
  year = {2011},
  month = may,
  location = {Dubai, UAE}
}

@MISC{esiea_french_kinect_sign,
  author = {Wassner, H.},
  title = {kinect + reseau de neurone = reconnaissance de gestes},
  howpublished = {http://tinyurl.com/5wbteug},
  month = may,
  year = {2011}
}


@ARTICLE{Starner_Real-time_1997,
  author = {Starner, T. and Pentland, A.},
  title = {Real-time american sign language recognition from video using hidden
    markov models},
  journal = {Computational Imaging and Vision},
  year = {1997},
  volume = {9},
  pages = {227 -- 244},
  abstract = {Hidden Markov models (HMM’s) have been used prominently and successfully
    in speech recognition and, more recently, in handwriting recognition.
    Consequently, they seem ideal for visual recognition of complex,
    structured hand gestures such as are found in sign language. We describe
    two experiments that. demonstrate a real-time HMM-based system for
    recognizing sentence level American Sign Language (ASL) without explicitly
    modeling the fingers. The first experiment tracks hands wearing colored
    gloves and attains a word accuracy of 99\%. The second experiment
    tracks hands without gloves and attains a word accuracy of 92\%.
    Both experiments have a 40 word lexicon},
  file = {:Starner_Real-time_1997.pdf:PDF},
  keywords = {sign-language-recognition hidden-markov-models},
  pdf = {Starner_Real-time_1997.pdf},
  publisher = {KLUWER ACADEMIC PUBLISHERS},
  review = {journal on the previous work in '95},
  timestamp = {2009.10.24}
}

@INPROCEEDINGS{Cooper_Large_2007,
  author = {Cooper, H. and Bowden, R.},
  title = {Large Lexicon Detection Of Sign Language},
  booktitle = PROCS # ICCV # {: Workshop Human Computer Interaction},
  pages = {88 -- 97},
  abstract = {This paper presents an approach to large lexicon sign recog-

    nition that does not require tracking. This overcomes the issues of
    how to

    accurately track the hands through self occlusion in unconstrained
    video,

    instead opting to take a detection strategy, where patterns of motion
    are

    identied. It is demonstrated that detection can be achieved with
    only

    minor loss of accuracy compared to a perfectly tracked sequence using

    coloured gloves. The approach uses two levels of classication. In
    the

    rst, a set of viseme classiers detects the presence of sub-Sign
    units of

    activity. The second level then assembles visemes into word level
    Sign

    using Markov chains. The system is able to cope with a large lexicon
    and

    is more expandable than traditional word level approaches. Using as
    few

    as 5 training examples the proposed system has classication rates
    as

    high as 74.3% on a randomly selected 164 sign vocabulary performing
    at

    a comparable level to other tracking based systems.},
  crossref = {ICCV07},
  doi = {10.1007/978-3-540-75773-3_10},
  file = {:Cooper_Large_2007.pdf:PDF},
  pdf = {Cooper_Large_2007.pdf}
}


@MISC{copy_cat,
  author = {Zafrulla, Z. and Brashear, H. and Presti, P. and Hamilton, H.   and Starner, T.},
  title = {CopyCat - Center for Accessible Technology in Sign},
  howpublished = {http://tinyurl.com/3tksn6s},
  month = Dec,
  year = {2010},
  url = {http://www.youtube.com/watch?v=qFH5rSzmgFE&feature=related}
}

@inproceedings{Zafrulla_American_2011,
 author = {Zafrulla, Z. and Brashear, H. and Starner, T. and Hamilton, H. and Presti, P.},
 title = {{American Sign Language} recognition with the {Kinect}},
 booktitle = {Proceedings of the 13th International Conference on Multimodal Interfaces},
 series = {ICMI '11},
 year = {2011},
 isbn = {978-1-4503-0641-6},
 location = {Alicante, Spain},
 pages = {279--286},
 numpages = {8},
 url = {http://doi.acm.org/10.1145/2070481.2070532},
 doi = {10.1145/2070481.2070532},
 acmid = {2070532},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {educational games, microsoft kinect, sign language verification},
}

@INPROCEEDINGS{Lyons_GART_2007,
  author = {Lyons, K. and Brashear, H. and Westeyn, T. L.  and Kim, J. S.  and Starner, T.},
  title = {GART: The Gesture and Activity Recognition Toolkit},
  booktitle = PROCS # INT # CONF # {HCI},
  year = {2007},
  pages = {718--727},
  month = jul,
  location = {Beijing, China}
}


@INCOLLECTION{Shoup_Phonological_1980,
  author = {Shoup, J. E. },
  title = {Phonological Aspects of Speech Recognition},
  booktitle = {Trends in Speech Recognition},
  publisher = {Prentice-Hall},
  year = {1980},
  editor = {Wayne A. Lea},
  pages = {125 -- 138},
  address = {Englewood Cliffs, NJ}
}


@INPROCEEDINGS{Freund_decision-theoretic_1997,
  author = {Freund, Y. and Schapire, R. E.},
  title = {A decision-theoretic generalization of on-line learning and an application
    to boosting},
  booktitle = PROCS # { European Conference on Computational Learning Theory},
  year = {1995},
  pages = {23 -- 37},
  address = {Barcelona, Spain},
  month = mar # { 13 -- 15},
  publisher = {Springer-Verlag},
  abstract = {In the first part of the paper we consider the problem of dynamically

    apportioning resources among a set of options in a worst-case on-line

    framework. The model we study can be interpreted as a broad, abstract

    extension of the well-studied on-line prediction model to a general

    decision-theoretic setting. We show that the multiplicative weight-

    update LittlestoneWarmuth rule can be adapted to this model, yielding

    bounds that are slightly weaker in some cases, but applicable to a
    con-

    siderably more general class of learning problems. We show how the

    resulting learning algorithm can be applied to a variety of problems,

    including gambling, multiple-outcome prediction, repeated games, and

    prediction of points in Rn. In the second part of the paper we apply
    the

    multiplicative weight-update technique to derive a new boosting algo-

    rithm. This boosting algorithm does not require any prior knowledge

    about the performance of the weak learning algorithm. We also study

    generalizations of the new boosting algorithm to the problem of

    learning functions whose range, rather than being binary, is an arbitrary

    finite set or a bounded segment of the real line.},
  file = {:Freund_decision-theoretic_1997.pdf:PDF},
  isbn = {3-540-59119-2}
}
@INPROCEEDINGS{Viola_Rapid_2001,
  author = {Viola, P. and Jones, M.},
  title = {Rapid Object Detection using a Boosted Cascade of Simple Features},
  volume = {1},
  pages = {511 -- 518},
  abstract = {This paper describes a machine learning approach for visual object
    detection which is capable of processing images extremely rapidly
    and achieving high detection rates. This work is distinguished by
    three key contributions. The first is the introduction of a new image
    representation called the "Integral Image" which allows the features
    used by our detector to be computed very quickly. The second is a
    learning algorithm, based on AdaBoost, which selects a small number
    of critical visual features from a larger set and yields extremely
    efficient classifiers[5]. The third contribution is a method for
    combining increasingly more complex classifiers in a "cascade" which
    allows background regions of the image to be quickly discarded while
    spending more computation on promising object-like regions. The cascade
    can be viewed as an object specific focus-of-attention mechanism
    which unlike previous approaches provides statistical guarantees
    that discarded regions are unlikely to contain the object of interest.
    In the domain of face detection the system yields detection rates
    comparable to the best previous systems. Used in real-time applications,
    the detector runs at 15 frames per second without resorting to image
    differencing or skin color detection},
  crossref = {CVPR01},
  file = {:Viola_Rapid_2001.pdf:PDF},
  keywords = {face-detector haar-wavelet real-time},
  pdf = {Viola_Rapid_2001.pdf},
  timestamp = {2009.10.24}
}
@ARTICLE{Hu_Visual_1962,
  author = {Hu, M. K.},
  title = {Visual Pattern Recognition by Moment Invariants},
  journal = {IRE Transactions on Information Theory},
  year = {1962},
  volume = {IT-8},
  pages = {179--187},
  month = {February},
  abstract = {planar geometric figures is presented. A fundamental

    theorem is established to relate such moment invariants to the wellknown

    algebraic invariants. Complete systems of moment invariants

    under translation, similitude and orthogonal transformations are

    derived. Some moment invariants under general two-dimensional

    linear transformations are also included.

    Both theoretical formulation and practical models of visual

    pattern recognition based upon these moment invariants are

    discussed. A simple simulation program together with its performance

    are also presented. It is shown that recognition of geometrical

    patterns and alphabetical characters independently of position, size

    and orientation can be accomplished. It is also indicated that

    generalization is possible to include invariance with parallel projection.},
  citeulike-article-id = {1145276},
  file = {:Hu_Visual_1962.pdf:PDF}
}

@INPROCEEDINGS{Roussos_Hand_2010,
  author = {Roussos, A. and Theodorakis, S. and Pitsikalis, V. and Maragos, P. },
  title = {Hand Tracking and Affine Shape-Appearance Handshape Sub-Units in
    Continuous Sign Language Recognition},
  booktitle = PROCS # INT # CONF # ECCV # WKSHP # { SGA},
  crossref = {ECCV10}
}

@ARTICLE{Elliott_D5-2_2001,
  author = {Elliott, R. and Glauert, J. and Kennaway, J. and Parsons, K.},
  title = {{D5-2: SiGML Definition} },
  journal = {ViSiCAST Project working document},
  year = {2001},
  owner = {Helen},
  timestamp = {2011.02.28}
}

@INPROCEEDINGS{Buehler_Learning_2009,
  author = {Buehler, P. and Everingham, M. and Zisserman, A.},
  title = {Learning sign language by watching {TV} (using weakly aligned subtitles)},
  pages = {2961 -- 2968},
  abstract = {The goal of this work is to automatically learn a large number of
    British Sign Language (BSL) signs from TV broadcasts. We achieve
    this by using the supervisory information available from subtitles
    broadcast simultaneously with the signing. This supervision is both
    weak and noisy: it is weak due to the correspondence problem since
    temporal distance between sign and subtitle is unknown and signing
    does not follow the text order; it is noisy because subtitles can
    be signed in different ways, and because the occurrence of a subtitle
    word does not imply the presence of the corresponding sign. The contributions
    are: (i) we propose a distance function to match signing sequences
    which includes the trajectory of both hands, the hand shape and orientation,
    and properly models the case of hands touching; (ii) we show that
    by optimizing a scoring function based on multiple instance learning,
    we are able to extract the sign of interest from hours of signing
    footage, despite the very weak and noisy supervision. The method
    is automatic given the English target word of the sign to be learnt.
    Results are presented for 210 words including nouns, verbs and adjectives},
  crossref = {CVPR09},
  file = {:Buehler_Learning_2009.pdf:PDF},
  keywords = {sign-language-recognition subtitles learning weakly-aligned},
  pdf = {Buehler_Learning_2009.pdf},
  timestamp = {2009.10.24}
}

@article{AmitGeman1997,
  author = {Amit, Y.  and Geman,  D.},
  title = {Shape quantization and recognition with randomized trees},
  journal = {Neural Computation},
  volume = {9},
  pages = {1545--1588},
  year = {1997}
}

@article{Breiman2001,
    author = {Breiman, L.},
    title = {Random Forests},
    journal = {Machine Learning},
    year = {2001},
    pages = {5--32}
}

@MANUAL{OpenNI2010,
  title = {OpenNI User Guide},
  organization = {OpenNI organization},
  month = {November},
  year = {2010},
  note = {Last viewed 20-04-2011 18:15},
  howpublished = {http://www.openni.org/documentation}
}

@MANUAL{PrimeSense2010,
  title = {Prime Sensor\texttrademark NITE 1.3 Algorithms notes},
  organization = {PrimeSense Inc.},
  year = {2010},
  note = {Last viewed 20-04-2011 18:15},
  howpublished = {http://www.primesense.com}
}

@INPROCEEDINGS{Ong_Learning_2011,
  author = {Ong, E. J. and Bowden, R.},
  title = {Learning Sequential Patterns for Lipreading},
  crossref = {BMVC11}
}

@INPROCEEDINGS{Ong_Sign_2012,
author = {Ong, E. J.  and Cooper, H. and Pugeault, N. and Bowden, R. },
title = {Sign Language Recognition using Sequential Pattern Trees},
crossref = {CVPR12}
}



@PROCEEDINGS{BMVC11,
  title = BMVC,
  year = {2011},
  address = {Dundee, UK},
  month = aug # { 29 -- } # sep # { 10},
  booktitle = PROCS # BMVC,
  owner = {Helen},
  timestamp = {2009.10.31}
}



@PROCEEDINGS{CVPR09,
  title = CVPR,
  year = {2009},
  address = {Miami, FL, USA},
  month = jun # { 20 -- 26},
  booktitle = PROCS # CVPR,
  owner = {Helen},
  timestamp = {2009.10.31}
}

@PROCEEDINGS{ICCV99,
  title = ICCV,
  year = {1999},
  address = {Corfu, Greece},
  month = sep # { 21 -- 24},
  booktitle = PROCS # ICCV,
  owner = {Helen},
  timestamp = {2009.10.31}
}

@PROCEEDINGS{BMVC04,
  title = BMVC,
  year = {2004},
  address = {Kingston, UK},
  month = sep # { 7 -- 9},
  booktitle = PROCS # BMVC,
  owner = {Helen},
  timestamp = {2009.10.31}
}

@PROCEEDINGS{FG08,
  title = FGR,
  year = {2008},
  address = {Amsterdam, The Netherlands},
  month = sep # { 17 -- 19},
  booktitle = PROCS # FGR,
  owner = {Helen},
  timestamp = {2009.10.31}
}

@PROCEEDINGS{CVPR11,
  title = CVPR,
  year = {2011},
  address = { Colorado Springs, CO, USA},
  month = jun # { 21 -- 23 },
  booktitle = PROCS # CVPR,
  owner = {Helen},
  timestamp = {2009.10.31}
}

@PROCEEDINGS{ICCV07,
  title = ICCV,
  year = {2007},
  address = {Rio de Janario, Brazil},
  month = oct # { 16 -- 19},
  booktitle = PROCS # ICCV,
  owner = {Helen},
  timestamp = {2009.10.31}
}

@PROCEEDINGS{CVPR01,
  title = CVPR,
  year = {2001},
  address = {Kauai, HI, USA},
  month = dec,
  booktitle = PROCS # CVPR,
  owner = {Helen},
  timestamp = {2009.10.31}
}
@PROCEEDINGS{ECCV10,
  title = ECCV,
  year = {2010},
  address = {Heraklion, Crete},
  month = sep # { 5 -- 11},
  booktitle = PROCS # ECCV,
  owner = {Helen},
  timestamp = {2009.10.31}
}

@article{metsis_puc_toappear,
  author =       {V. Metsis and D. Kosmopoulos and V. Athitsos and F. Makedon},
  title =        {Non-Invasive Analysis of Sleep Patterns via Multimodal Sensor Input},
  journal = {Journal of Personal and Ubiquitous Computing},
  volume = {},
  number = {},
  pages = "",
  year =         "accepted June 2012, to appear"
}


@article{stefan_tkde2013,
  author =       {A. Stefan and V. Athitsos and G. Das},
  title =        {The Move-Split-Merge Metric for Time Series},
  journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},
  volume = {25},
  number = {6},
  pages = "1425-1438",
  year =  {2013}
}


@inproceedings{conly_petra2013,
  author    = {C. Conly and P. Doliotis and P. Jangyodsuk and R. Alonzo and  V. Athitsos},
  title     = {Toward a {3D} Body Part Detection Video Dataset and Hand Tracking Benchmark},
  booktitle = {Pervasive Technologies Related to Assistive Environments (PETRA)},
  year      = {2013}
 }


@inproceedings{kotsifakos_sdm2013,
  author    = {A. Kotsifakos and  P. Papapetrou and V. Athitsos},
  title     = {IBSM: Interval-Based Sequence Matching},
  booktitle = {SIAM International Conference on Data Mining (SDM)},
  year      = {2013}
 }


@article{zhu_pvldb2012,
  author =       {H. Zhu and G. Kollios and V. Athitsos},
  title =        {A Generic Framework for Efficient and Effective Subsequence Retrieval},
  journal   = {Proceedings of the Very Large Database Endowment (PVLDB)},
  volume = {5},
  number = {11},
  pages = "1579-1590",
  year =         "2012"
}


@inproceedings{zhang_icpr2012,
  author    = {Z. Zhang and W. Liu and V. Metsis and V. Athitsos},
  title     = {A Viewpoint-Independent Statistical Method for Fall Detection},
  booktitle = {International Conference on Pattern Recognition (ICPR)},
  year      = {2012}
 }


@inproceedings{kotsifakos_vldb2012,
  author    = {A. Kotsifakos and P. Papapetrou and J. Hollm\'{e}n and D. Gunopulos and V. Athitsos and G. Kollios},
  title     = {Hum-a-song: A Subsequence Matching with Gaps-Range-Tolerances Query-By-Humming System},
  booktitle = {International Conference on Pattern Recognition (ICPR)},
  year      = {2012}
 }


@inproceedings{doliotis_isvc2012,
  author    = {P. Doliotis and V. Athitsos and D. Kosmopoulos and S. Perantonis},
  title     = {Hand Shape and 3D Pose Estimation using Depth Data from a Single Cluttered Frame},
  booktitle = {International Symposium on Visual Computing (ISVC)},
  year      = {2012}
 }


@inproceedings{guyon_grw2012,
  author    = {I. Guyon and
               V. Athitsos and
               P. Jangyodsuk and
               B. Hamner and
               H. J. Escalante},
  title     = {{ChaLearn} gesture challenge: Design and first results},
  booktitle = {CVPR Workshop on Gesture Recognition},
  year      = {2012}
 }


@article{papapetrou_tods2011,
  author =       {P. Papapetrou and V. Athitsos and M. Potamias and G. Kollios and D. Gunopulos},
  title =        {Embedding-based Subsequence Matching in Time Series Databases},
  journal = {ACM Transactions on Database Systems (TODS)},
  volume = {36},
  number = {3},
  pages = "Article 17",
  year =         "2011"
}




@inproceedings{doliotis_petra2011,
 author = {P. Doliotis and A. Stefan and C. Mcmurrough and D. Eckhard and Vassilis Athitsos},
 title = {Comparing Gesture Recognition Accuracy Using Color and Depth Information},
  booktitle = {Conference on Pervasive Technologies Related to Assistive Environments (PETRA)},
  year =         "2011"
}




@inproceedings{kotsifakos_petra2011,
 author = {A. Kotsifakos and V. Athitsos and P. Papapetrou and J. Hollm\'{e}n and Dimitrios Gunopulos},
 title = {Model-Based Search in Large Time Series Databases},
  booktitle = {Conference on Pervasive Technologies Related to Assistive Environments (PETRA)},
  year =         "2010"
}




@inproceedings{wang_sga2010,
 author = {H. Wang and A. Stefan and S. Moradi and V. Athitsos and C. Neidle and F. Kamangar},
 title = {A System for Large Vocabulary Sign Search},
  booktitle = "Workshop on Sign, Gesture and Activity (SGA)",
  year =         "2010"
}




@article{athitsos_puc2010,
  author =       {V. Athitsos and H. Wang and A. Stefan},
  title =        {A Database-Based Framework for Gesture Recognition},
  journal = {Journal of Personal and Ubiquitous Computing},
  volume = {14},
  number = {6},
  pages = "511--526",
  year =         "2010"
}




@inproceedings{athitsos_cslt2010,
 author = {V. Athitsos and C. Neidle and S. Sclaroff and J. Nash and A. Stefan and A. Thangali and H. Wang and Q. Yuan},
 title = {Large Lexicon Project: {American Sign Language} Video Corpus and Sign Language Indexing/Retrieval Algorithms},
  booktitle = "Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies (CSLT)",
  pages = "11--14",
  year =         "2010"
}




@inproceedings{zhang_petra2010,
 author = {Z. Zhang and E. Becker and R. Arora and V. Athitsos},
 title = {Experiments with Computer Vision Methods for Fall Detection},
  booktitle = {Conference on Pervasive Technologies Related to Assistive Environments (PETRA)},
  year =         "2010"
}




@inproceedings{lijffijt_weaae2010,
 author = {J. Lijffijt and P. Papapetrou and J. Hollmen and V. Athitsos},
 title = {Benchmarking Dynamic Time Warping for Music Retrieval},
  booktitle = "Workshop on Workflow and Event Analysis for Assistive Environments",
  year =         "2010"
}


@inproceedings{wang_uahci2009,
 author = {H. Wang and A. Stefan and V. Athitsos},
 title = {A Similarity Measure for Vision-Based Sign Recognition},
  booktitle = "International Conference on Universal Access in Human-Computer Interaction (UAHCI)",
  pages = "607--616",
  year =         "2009"
}


@article{alon_pami2009,
  author =       {J. Alon and V. Athitsos and Q. Yuan and S. Sclaroff},
  title =        {A Unified Framework for Gesture Recognition and Spatiotemporal Gesture Segmentation},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume = {31},
  number = {9},
  pages = "1685--1699",
  year =         "2009"
}




@article{papapetrou_pvldb2009,
  author    = {P. Papapetrou and
               V. Athitsos and
               G. Kollios and
               D. Gunopulos},
  title     = {Reference-Based Alignment in Large Sequence Databases},
  journal   = {Proceedings of the Very Large Database Endowment (PVLDB)},
  volume    = {2},
  number    = {1},
  year      = {2009},
  pages     = {205-216}
}




@inproceedings{stefan_cvpr2009,
  author =       {A. Stefan and V. Athitsos and Q. Yuan and S. Sclaroff},
  title =        "Reducing JointBoost-Based Multiclass Classification to Proximity Search",
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year =         {2009}
}




@inproceedings{wu_eccv2008,
  author =       {Z. Wu and M. Betke and J. Wang and V. Athitsos and S. Sclaroff},
  title =        "Tracking with Dynamic Hidden State Shape Models",
  booktitle = "European Conference on Computer Vision (ECCV)",
  pages = "643--656",
  year =         {2008}
}




@inproceedings{Athitsos_cvpr4hb2008,
  author =       {V. Athitsos and C. Neidle and S. Sclaroff and J. Nash and A. Stefan and Q. Yuan and A. Thangali},
  title =        {The {American Sign Language} Lexicon Video Dataset},
  booktitle = {IEEE Workshop on Computer Vision and Pattern Recognition for Human Communicative Behavior Analysis (CVPR4HB)},
  year =         {2008}
}




@inproceedings{potamias_petra2008,
  author =       {M. Potamias and V. Athitsos},
  title =        "Nearest Neighbor Search Methods for Handshape Recognition",
  booktitle = {Conference on Pervasive Technologies Related to Assistive Environments (PETRA)},
  year =         {2008}
}




@inproceedings{stefan_petra2008,
  author = {A. Stefan and V. Athitsos and J. Alon and S. Sclaroff},
  title = {Translation and scale-invariant gesture recognition in complex scenes},
  booktitle = {Conference on Pervasive Technologies Related to Assistive Environments (PETRA)},
  year =         {2008}
}




@inproceedings{stefan_petra2009,
  author = {A. Stefan and H. Wang and V. Athitsos},
  title = {Towards Automated Large Vocabulary Gesture Search},
  booktitle = {Conference on Pervasive Technologies Related to Assistive Environments (PETRA)},
  year =         {2009}
}




@inproceedings{Athitsos_SIGMOD2008,
  author =       {V. Athitsos and P. Papapetrou and M. Potamias and G. Kollios and D. Gunopulos},
  title =        {Approximate Embedding-Based Subsequence Matching of Time Series},
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  pages = "365--378",
  year =         {2008}
}




@article{Athitsos_PAMI2008,
  author =       {V. Athitsos and J. Alon and S. Sclaroff and G. Kollios},
  title =        {BoostMap: An Embedding Method for Efficient Nearest Neighbor Retrieval},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume = {30},
  number = {1},
  pages = "89--104",
  year =         "2008"
}




@article{wang_pami2008,
  author =       {J. Wang and V. Athitsos and S. Sclaroff and M. Betke},
  title =        {Detecting Objects of Variable Shape Structure With Hidden State Shape Models},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume = {30},
  number = {3},
  pages = "477--492",
  year =         "2008"
}




@inproceedings{Athitsos_ICDE2008,
  author =       {V. Athitsos and M. Potamias and P. Papapetrou and G. Kollios},
  title =        {Nearest Neighbor Retrieval Using Distance-Based Hashing},
  booktitle = {IEEE International Conference on Data Engineering (ICDE)},
  pages = "326--336",
  year =         {2008},
}


@inproceedings{Athitsos_ICCV2007,
  author =       {V. Athitsos and A. Stefan and Q. Yuan and S. Sclaroff},
  title =        "{ClassMap}: Efficient Multiclass Recognition via Embeddings",
  booktitle = {IEEE International Conference on Computer Vision (ICCV)},
  year =         {2007},
}






@PhdThesis{Athitsos_thesis,
  author =       {Vassilis Athitsos},
  title =        {Learning Embeddings for Indexing, Retrieval, and Classification, with Applications to Object and Shape Recognition in Image Databases},
  school =       {Boston University},
  year =         {2006},
}






@article{Athitsos_tods2007,
  author =       {V. Athitsos and M. Hadjieleftheriou and G. Kollios and S. Sclaroff},
  title =        "Query-Sensitive Embeddings",
  journal = "{ACM} Transactions on Database Systems (TODS)",
  year =         "2007",
  volume = {32},
  number = {2},
}


@inproceedings{Athitsos_eccv2006,
  author =       {V. Athitsos and J. Wang and S. Sclaroff and M. Betke},
  title =        "Detecting Instances of Shape Classes That Exhibit Variable Structure",
  booktitle = "European Conference on Computer Vision (ECCV)",
  pages = "121--134",
  year =         {2006},
}


@inproceedings{Athitsos_cvpr2005,
  author =       {V. Athitsos and J. Alon and S. Sclaroff},
  title =        "Efficient Nearest Neighbor Classification Using a Cascade of Approximate Similarity Measures",
  booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
  pages = "486--493",
  year =         {2005},
}


@inproceedings{Athitsos_cvpr2005b,
  author =       {V. Athitsos and J. Alon and S. Sclaroff},
  title =        "Efficient Nearest Neighbor Classification Using a Cascade of Approximate Similarity Measures",
  booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
  pages = "486--493",
  year =         {2005},
}


@inproceedings{Athitsos_lcvpr2005,
  author =       {V. Athitsos and S. Sclaroff},
  title =        "Boosting Nearest Neighbor Classifiers for Multiclass Recognition",
  booktitle = "IEEE Workshop on Learning in Computer Vision and Pattern Recognition",
  year =         {2005},
}


@inproceedings{Athitsos_SIGMOD2005,
  author =       {V. Athitsos and M. Hadjieleftheriou and G. Kollios and S. Sclaroff},
  title =        "Query-Sensitive Embeddings",
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  pages = "706--717",
  year =         {2005},
}




@inproceedings{alon_wmcv2005,
  author =       {J. Alon and V. Athitsos and Q. Yuan and S. Sclaroff},
  title =        "Simultaneous Localization and Recognition of Dynamic Hand Gestures",
  booktitle = {IEEE Motion Workshop},
  pages = "254--260",
  year =         {2005},
}




@inproceedings{alon_hci2005,
  author =       {J. Alon and V. Athitsos and S. Sclaroff},
  title =        "Accurate and Efficient Gesture Spotting via Pruning and Subgesture Reasoning",
  booktitle = {IEEE Workshop on Human Computer Interaction},
  pages = "189--198",
  year =         {2005},
}




@inproceedings{alon_icdar2005,
  author =       {J. Alon and V. Athitsos and S. Sclaroff},
  title =        "Online and Offline Character Recognition Using Alignment to Prototypes",
  booktitle = {International Conference on Document Analysis and Recognition},
  pages = "839-843",
  year =         {2005},
}


@inproceedings{Athitsos_avivdilib2005,
  author =       {V. Athitsos and J. Alon and S. Sclaroff and G. Kollios},
  title =        "Filtering Methods for Similarity-Based Multimedia Retrieval",
  booktitle = {International Workshop on Audio-Visual Content and Information Visualization in Digital Libraries (AVIVDiLib)},
  year =         {2005},
}


@inproceedings{Athitsos_cues2001,
AUTHOR = "Vassilis Athitsos and Stan Sclaroff",
TITLE = "3{D} Hand Pose Estimation by Finding Appearance-Based
Matches in a Large Database of Training Views",
BOOKTITLE = "IEEE Workshop on Cues in Communication",
YEAR="2001"
}


@inproceedings{Athitsos_cues2001_short,
AUTHOR = "V. Athitsos and S. Sclaroff",
TITLE = "3{D} Hand Pose Estimation by Finding Appearance-Based
Matches in a Large Database of Training Views",
BOOKTITLE = "IEEE Workshop on Cues in Communication",
YEAR="2001"
}


@inproceedings{anonymous_fg2002,
AUTHOR = "The Authors",
TITLE = "",
BOOKTITLE = "",
YEAR="2002"
}


@inproceedings{Athitsos_fg2002,
AUTHOR = "V. Athitsos and S. Sclaroff",
TITLE = "An Appearance-Based Framework for 3{D} Hand Shape
Classification and Camera Viewpoint Estimation",
BOOKTITLE = "Automatic Face and Gesture Recognition",
PAGES = "45--50",
YEAR="2002"
}


@inproceedings{anonymous_cvpr2003,
AUTHOR = "The Authors",
TITLE = "",
BOOKTITLE = "",
PAGES = "",
YEAR = "2003"
}




@InProceedings{Athitsos_gw2003,
AUTHOR = "V. Athitsos and S. Sclaroff",
TITLE = "Database Indexing Methods for {3D} Hand Pose Estimation",
BOOKTITLE = "Gesture Workshop",
pages = "288-299",
YEAR = "2003",
publisher = {Springer-Verlag Heidelberg}
}


@inproceedings{Athitsos_cvpr2003_short,
AUTHOR = "V. Athitsos and S. Sclaroff",
TITLE = "Estimating Hand Pose from a Cluttered Image",
booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
VOLUME = "2",
PAGES = "432-439",
YEAR = "2003"
}


@inproceedings{Athitsos_cvpr2003,
AUTHOR = "V. Athitsos and S. Sclaroff",
TITLE = "Estimating Hand Pose from a Cluttered Image",
BOOKTITLE = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
VOLUME = "2",
PAGES = "432-439",
YEAR = "2003"
}


@inproceedings{anonymous_joni_cvpr2004,
AUTHOR = "",
TITLE = "",
BOOKTITLE = "",
PAGES = "",
YEAR = "2003"
}


@TechReport{Athitsos_tech_cues2001,
  author =       {Vassilis Athitsos and Stan Sclaroff},
  title =        "3{D} Hand Pose Estimation by Finding Appearance-Based
Matches in a Large Database of Training Views",
  institution =  {Computer Science Department, Boston University},
  number =       {21},
  year =         {2001},
}


@TechReport{Athitsos_tech_cvpr2004,
  author =       {V. Athitsos and J. Alon and S. Sclaroff and G. Kollios},
  title =        "{BoostMap}: A Method for Efficient Approximate Similarity Rankings",
  institution =  {Computer Science Department, Boston University},
  number =       {23},
  year =         {2003},
}


@inproceedings{Athitsos_cvpr2004,
  author =       {V. Athitsos and J. Alon and S. Sclaroff and G. Kollios},
  title =        "{BoostMap}: A Method for Efficient Approximate Similarity Rankings",
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages = "268--275",
  year =         {2004},
}


@inproceedings{Athitsos_cvpr2004b,
  author =       {V. Athitsos and J. Alon and S. Sclaroff and G. Kollios},
  title =        "{BoostMap}: A Method for Efficient Approximate Similarity Rankings",
  booktitle = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
  pages = "268--275",
  year =         {2004},
}








@inproceedings{anonymous_cues2001,
AUTHOR = "The Authors",
TITLE = "Omitted",
BOOKTITLE = "Omitted",
YEAR="2001"
}




@TechReport{anonymous_tech_fg2002,
  author =       {The Authors},
  title =        {},
  institution =  {},
  year =         {2001},
}


@TechReport{Athitsos_tech_fg2002,
  author =       {Vassilis Athitsos and Stan Sclaroff},
  title =        {An Appearance-Based Framework for 3{D} Hand Shape
Classification and Camera Viewpoint Estimation},
  institution =  {Computer Science Department, Boston University},
  number =       {22},
  year =         {2001},
}


@TechReport{Athitsos_tech_fg2002_short,
  author =       {V. Athitsos and S. Sclaroff},
  title =        {An Appearance-Based Framework for 3{D} Hand Shape
Classification and Camera Viewpoint Estimation},
  institution =  {Computer Science Department, Boston University},
  number =       {22},
  year =         {2001},
}


@TechReport{Athitsos_kdd2004,
  author =       {V. Athitsos and J. Alon and S. Sclaroff and G. Kollios},
  title =        {Learning {Euclidean} Embeddings for Indexing and Classification},
  institution =  {Computer Science Department, Boston University},
  number =       {14},
  year =         {2004},
}










@inProceedings {dreuw_lrec2008,
author= {Dreuw, P. and Neidle, C. and Athitsos, V. and Sclaroff, S. and Ney, H.},
title= {Benchmark Databases for Video-Based Automatic Sign Language Recognition},
booktitle= {International Conference on Language Resources and Evaluation},
year= 2008
}




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@InProceedings{hienz_icmi1999_long,
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@article{s_hu1962,
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@inproceedings{huang_correlograms,
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@InProceedings{indyk1998,
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@InProceedings{s_indyk1998,
  author =       {P. Indyk},
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@PhdThesis{indyk_thesis,
  author =       {Piotr Indyk},
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  school =       {Stanford University},
  year =         {2000},
}




@PhdThesis{s_indyk_thesis,
  author =       {P. Indyk},
  title =        {High-dimensional Computational Geometry},
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}




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@techReport{kohler2,
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@inproceedings{maccormick,
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@TechReport{jones_merl2003,
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@InProceedings{yu_es2005,
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@inproceedings{wang_fg2002_long,
  author    = {Chunli Wang and
               Shiguang Shan and
               Wen Gao},
  title     = {An Approach Based on Phonemes to Large Vocabulary {Chinese
               Sign Language} Recognition.},
  booktitle = {Automatic Face and Gesture Recognition},
  year      = {2002},
  pages     = {411-416}
}


@inproceedings{wang_fg2002,
  author    = {C. Wang and
               S. Shan and
               W. Gao},
  title     = {An Approach Based on Phonemes to Large Vocabulary {Chinese
               Sign Language} Recognition},
  booktitle = {Automatic Face and Gesture Recognition},
  year      = {2002},
  pages     = {411-416}
}


@inproceedings{vogler_gw2003_long,
  author    = {Christian Vogler and
               Dimitris N. Metaxas},
  title     = {Handshapes and Movements: Multiple-Channel {American Sign
               Language} Recognition},
  booktitle = {Gesture Workshop},
  year      = {2003},
  pages     = {247-258}
}


@inproceedings{vogler_gw2003,
  author    = {C. Vogler and
               D. N. Metaxas},
  title     = {Handshapes and Movements: Multiple-Channel {American Sign
               Language} Recognition},
  booktitle = {Gesture Workshop},
  year      = {2003},
  pages     = {247-258}
}


@article{vogler_cviu2001_long,
  author    = {Christian Vogler and
               Dimitris N. Metaxas},
  title     = {A Framework for Recognizing the Simultaneous Aspects of
               American Sign Language},
  journal   = {Computer Vision and Image Understanding},
  volume    = {81},
  number    = {3},
  year      = {2001}
}


@article{vogler_cviu2001,
  author    = {C. Vogler and
               D. N. Metaxas},
  title     = {A Framework for Recognizing the Simultaneous Aspects of
               {American Sign Language}},
  journal   = {Computer Vision and Image Understanding (CVIU)},
  volume    = {81},
  number    = {3},
  year      = {2001}
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@inproceedings{fang_icmi2003_long,
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 title = {Large vocabulary sign language recognition based on hierarchical decision trees},
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 year = {2003},
 pages = {125--131}
}


@inproceedings{fang_icmi2003,
 author = {G. Fang and W. Gao and D. Zhao},
 title = {Large vocabulary sign language recognition based on hierarchical decision trees},
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 pages = {125--131}
}


@inproceedings{hernandez_icmi2005_long,
 author = {Jose L. Hernandez-Rebollar},
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 pages = {288--292}
}


@inproceedings{hernandez_icmi2005,
 author = {J. L. Hernandez-Rebollar},
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 pages = {288--292}
}


@inproceedings{vogler_iccv1999,
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  pages     = {116-122}
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@InProceedings{kadir_bmvc2004,
  author =       {T. Kadir and R. Bowden and E. Ong and A. Zisserman},
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  pages =     {939-948},
  year =      {2004},
  volume =    {2}
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@inproceedings{yao_icpr2006_long,
  author    = {Guilin Yao and
               Hongxun Yao and
               Xin Liu and
               Feng Jiang},
  title     = {Real Time Large Vocabulary Continuous Sign Language Recognition
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  booktitle = {International Conference on Pattern Recognition},
  year      = {2006},
  volume = {3},
  pages     = {312-315}
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@inproceedings{yao_icpr2006,
  author    = {G. Yao and
               H. Yao and
               X. Liu and
               F. Jiang},
  title     = {Real Time Large Vocabulary Continuous Sign Language Recognition
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  booktitle = {International Conference on Pattern Recognition},
  year      = {2006},
  volume = {3},
  pages     = {312-315}
}


@inproceedings{gao_fg2004_long,
  author    = {Wen Gao and
               Gaolin Fang and
               Debin Zhao and
               Yiqiang Chen},
  title     = {Transition Movement Models for Large Vocabulary Continuous
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  booktitle = {Automatic Face and Gesture Recognition},
  year      = {2004},
  pages     = {553-558}
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@inproceedings{gao_fg2004,
  author    = {W. Gao and
               G. Fang and
               D. Zhao and
               Y. Chen},
  title     = {Transition Movement Models for Large Vocabulary Continuous
               Sign Language Recognition.},
  booktitle = {Automatic Face and Gesture Recognition},
  year      = {2004},
  pages     = {553-558}
}


@inproceedings{wu_sigmod2005_long,
  author    = {Huanmei Wu and
               Betty Salzberg and
               Gregory C. Sharp and
               Steve B. Jiang and
               Hiroki Shirato and
               David R. Kaeli},
  title     = {Subsequence Matching on Structured Time Series Data.},
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2005},
  pages     = {682-693}
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@inproceedings{wu_sigmod2005,
  author    = {H. Wu and
               B. Salzberg and
               G. C. Sharp and
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               H. Shirato and
               D. R. Kaeli},
  title     = {Subsequence Matching on Structured Time Series Data.},
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2005},
  pages     = {682-693}
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@inproceedings{moon_icde2001_long,
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               Woong-Kee Loh},
  title     = {Duality-Based Subsequence Matching in Time-Series Databases.},
  booktitle = {IEEE International Conference on Data Engineering (ICDE)},
  year      = {2001},
  pages     = {263-272}
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@inproceedings{moon_icde2001,
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  title     = {Duality-Based Subsequence Matching in Time-Series Databases.},
  booktitle = {IEEE International Conference on Data Engineering (ICDE)},
  year      = {2001},
  pages     = {263-272}
}


@inproceedings{moon_sigmod2002_long,
  author    = {Yang-Sae Moon and
               Kyu-Young Whang and
               Wook-Shin Han},
  title     = {General match: a subsequence matching method in time-series
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  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2002},
  pages     = {382-393}
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@inproceedings{moon_sigmod2002,
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               K.Y. Whang and
               W.S. Han},
  title     = {General match: a subsequence matching method in time-series
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  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2002},
  pages     = {382-393}
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@inproceedings{faloutsos_sigmod1994_long,
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@inproceedings{faloutsos_sigmod1994,
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@inproceedings{sakurai_pods2005_long,
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               Masatoshi Yoshikawa and
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  booktitle = {Principles of Database Systems (PODS)},
  year      = {2005},
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@inproceedings{sakurai_pods2005,
  author    = {Y. Sakurai and
               M. Yoshikawa and
               C. Faloutsos},
  title     = {{FTW}: fast similarity search under the time warping distance},
  booktitle = {Principles of Database Systems (PODS)},
  year      = {2005},
  pages     = {326-337}
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@inproceedings{palpanas_vldb2004,
  author    = {E. J. Keogh and
               T. Palpanas and
               V. B. Zordan and
               D. Gunopulos and
               M. Cardle},
  title     = {Indexing Large Human-Motion Databases.},
  booktitle = "International Conference on Very Large Databases (VLDB)",
  year      = {2004},
  pages     = {780-791}
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@inproceedings{zhu_sigmod2003_long,
  author    = {Yunyue Zhu and
               Dennis Shasha},
  title     = {Warping Indexes with Envelope Transforms for Query by Humming},
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2003},
  pages     = {181-192}
}


@inproceedings{zhu_sigmod2003,
  author    = {Y. Zhu and
               D. Shasha},
  title     = {Warping Indexes with Envelope Transforms for Query by Humming.},
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2003},
  pages     = {181-192}
}


@inproceedings{rath_cvpr2003,
  author    = {T. M. Rath and
               R. Manmatha},
  title     = {Word Image Matching Using Dynamic Time Warping.},
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  volume = {2},
  year      = {2003},
  pages     = {521-527}
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@inproceedings{park_sac2001,
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  booktitle = {Symposium on Applied Computing},
  year      = {2001},
  pages     = {248-252}
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@article{park_is2003,
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@Book{battison_1978,
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@article{cui_cviu2000,
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@inproceedings{rafiei_sigmod1997,
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@inproceedings{castelli_pris2006,
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@inproceedings{wang_cvpr2006,
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@article{quattoni_pami2007,
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%
% beginning of references for TKDD submission on Boosted Ranking Functions
%
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%
% end of references for TKDD submission on Boosted Ranking Functions
%
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%
% beginning of references for PETRA 2010 paper on Fall Detection
%
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  booktitle = {IEEE Conference on Engineering in Medicine and Biology Society},
  pages = "3551--3554",
  year =         "2005"
}


@inproceedings{Ivan_ICCV2007,
  author =       {Ivan Laptev and Patrick Perez},
  title =        "Retrieving actions in movies",
  booktitle = {IEEE International Conference on Computer Vision (ICCV)},
  year =         {2007}
}


@inproceedings{Ivan_cvpr2008,
  author =       {Ivan Laptev and Marcin Marszalek and Cordelia Schmid and Benjamin Rozenfeld},
  title =        "Learning realistic human actions from vidoes",
  booktitle = "IEEE Conference on Computer Vision and Pattern Recognition",
  year =         {2008}
}


@article{laptev_ijcv2005,
  author    = {I. Laptev},
  title     = {On Space-Time Interest Points},
  journal   = {International Journal of Computer Vision (IJCV)},
  volume    = {64},
  number    = {2-3},
  year      = {2005},
  pages     = {107-123}
}


@article{wu_biome2000,
  author = {Ge Wu},
  title = {Distinguishing fall activities from normal activities by velocity characteristics},
  journal = {Journal of Biomechanics},
  volume = {33},
  number = {11},
  year = {2000},
  pages = {1497--1500}
}


@inproceedings{Rougier,
  author    =    {Caroline Rougier and Jean Meunier},
  title      =    {Demo: Fall detection using 3D head trajectory extracted from a single camera video sequence},
  booktitle  =    {International Workshop on Video Processing for Security(VP4S-06)},
  year       = {2006}
}


@article{Lee05,
        AUTHOR = "D. Lee",
        TITLE = "Effective Gaussian Mixture Learning for Video Background Subtraction",
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
        VOLUME = "27",
        YEAR = "2005",
        NUMBER = "5",
        MONTH = "May",
        PAGES = "827-832"}


@article{zhang06,
        AUTHOR = "Tong Zhang and Jue Wang and Ping Liu and Jing Hou",
        TITLE = "Fall Detection by Embedding an Accelerometer in Cellphone and Using KFD Algorithm",
  journal = {International Journal of Computer Science and Network Security},
        VOLUME = "6",
        YEAR = "2006",
        NUMBER = "10",
        MONTH = "October",
        PAGES = "277-284"}


@article{Lindemann05,
        AUTHOR = "U. Lindemann and A. Hock and M. Stuber and W. Keck and C. Becker",
        TITLE = "Evaluation of a fall detector based on accelerometers: A pilot study",
  journal = {Medical and Biological Engineering and Computing},
        VOLUME = "43",
        YEAR = "2005",
        NUMBER = "5",
        MONTH = "October",
        PAGES = "548-551"}


@article{Bourke06,
        AUTHOR = "A.k. Bourke and J.V. O'Brien and G.M. Lyons",
        TITLE = "Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm",
  journal = {GAIT POSTURE},
        VOLUME = "26",
        YEAR = "2006",
        ISSUE = "2",
        MONTH = "July",
        PAGES = "194-199"}


@article{Bourke07,
        AUTHOR = "A. Bourke and G. Lyons",
        TITLE = "A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor",
  journal = {Medical Engineering \& Physics},
        VOLUME = "30",
        YEAR = "2007",
        ISSUE = "1",
        MONTH = "January",
        PAGES = "84-90"}


@inproceedings{Noury03,
  author    =    {N.Noury and P.Barralon and G.Virone and P.Boissy and M.Hamel and P.Rumeau},
  title      =    {A smart sensor based on rules and its evaluation in daily routines},
  booktitle  =    {IEEE conference on Engineering in Medicine and Biology Society},
  year       = {2003}
  }




@inproceedings{Nait04,
  author    =    {Hammadi Nait-Charif and Stephen J. McKenna},
  title      =    {Activity summarisation and fall detection in a supportive home environment},
  booktitle  =    {Internation Conference on Pattern Recognition(ICPR)},
  year       = {2004}
  }




@inproceedings{Jansen06,
  author    =    {B. Jansen and R. Deklerck},
  title      =    {Home monitoring of elderly people with 3d camera technology},
  booktitle  =    {Proceedings of the first BENELUX biomedical engineering symposium, Brussels, Belgium},
  year       = {2006}
  }


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% end of references for PETRA 2010 paper on Fall Detection
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% beginning of references for TODS 2010 paper on
% subsequence matching
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


@inproceedings{keogh_sdm2005,
  author    = {C. Ratanamahatana and
               E. J. Keogh},
  title     = {Three Myths about Dynamic Time Warping Data Mining},
  booktitle = {SIAM International Data Mining Conference (SDM)},
  year      = {2005}
}




@inproceedings{ChanF99,
  author    = {K.-P. Chan and
               A. W.-C. Fu},
  title     = {Efficient Time Series Matching by Wavelets},
  booktitle = {IEEE International Conference on Data Engineearing (ICDE)},
  year      = {1999},
  pages     = {126-133}
}




@inproceedings{VlachosGK02,
  author    = {M. Vlachos and
               D. Gunopulos and
               G. Kollios},
  title     = {Discovering Similar Multidimensional Trajectories},
  booktitle = {IEEE International Conference on Data Engineering (ICDE)},
  year      = {2002},
  pages     = {673-684}
}




@inproceedings{ChenCCO09,
   author    = {Yueguo Chen and
                Gang Chen and
                Ke Chen and
                Beng Chin Ooi},
   title     = {Efficient Processing of Warping Time Series Join of Motion Capture Data},
   booktitle = {ICDE},
   year      = {2009},
   pages     = {1048-1059}
}




@inproceedings{ChenN04,
  author    = {L. Chen and
               R. T. Ng},
  title     = {On The Marriage of Lp-norms and Edit Distance},
  booktitle = "International Conference on Very Large Databases (VLDB)",
  year      = {2004},
  pages     = {792-803}
}




@inproceedings{LateckiMWLRK05,
  author    = {L. Latecki and
               V. Megalooikonomou and
               Q. Wang and
               R. Lak{\"a}mper and
               C. Ratanamahatana and
               E. Keogh},
  title     = {Elastic Partial Matching of Time Series},
  booktitle = {European Conference on Principles of Data Mining and Knowledge Discovery (PKDD)},
  year      = {2005},
  pages     = {577-584}
}




@inproceedings{MorseP07,
  author    = {M. Morse and
               J. Patel},
  title     = {An efficient and accurate method for evaluating time series
               similarity},
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2007},
  pages     = {569-580}
}



@inproceedings{Keogh00scaling,
  author = "E. Keogh and M. Pazzani",
  title = {Scaling up Dynamic Time Warping for Data Mining Applications},
    booktitle = "{ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining",
  year = 2000
}




@inproceedings{ChenOO05,
  author    = {L. Chen and
               M. T. {\"O}zsu and
               V. Oria},
  title     = {Robust and Fast Similarity Search for Moving Object Trajectories},
  booktitle = {ACM International Conference on Management of Data (SIGMOD)},
  year      = {2005},
  pages     = {491-502}
}




@article{FuKLRW08,
  author    = {A. W.-C. Fu and
               E. Keogh and
               L. Y. H. Lau and
               C. Ratanamahatana and
               R. C.-W. Wong},
  title     = {Scaling and time warping in time series querying},
  journal   = {The Very Large Databases (VLDB) Journal},
  volume    = {17},
  number    = {4},
  year      = {2008},
  pages     = {899-921}
}




@inproceedings{Keogh93segmentingtime,
    AUTHOR = {E. Keogh and S. Chu and D. Hart and M. Pazzani},
    TITLE = {Segmenting Time Series: A Survey and Novel Approach},
    BOOKTITLE = {In an Edited Volume, Data mining in Time Series Databases. Published by World Scientific},
    YEAR = {1993},
    PAGES = {1--22},
    PUBLISHER = {Publishing Company}
}




@inproceedings{Bingham06segmentationand,
    AUTHOR = "E. Bingham and A. Gionis and N. Haiminen and H. Hiisil{\"{a}} and H. Mannila and E. Terzi",
    TITLE = "Segmentation and dimensionality reduction",
  booktitle = {SIAM International Data Mining Conference (SDM)},
    YEAR = "2006"
}




@inproceedings{LianC08,
  author    = {X. Lian and
               L. Chen },
  title     = {Similarity Search in Arbitrary Subspaces Under Lp-Norm},
  booktitle = {IEEE International Conference on Data Engineearing (ICDE)},
  year      = {2008},
  pages     = {317-326}
}




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% beginning of references for ECCV 2010 paper on
% the ASL sign look up project
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


% it is a similarity measure, but pretty simple one.
% requires accurate silhouette extraction (we just know bounding box).
@article{gorelick_pami2007,
  author = {L. Gorelick and M. Blank and E. Shechtman and M. Irani and R. Basri},
  title = {Actions as Space-Time Shapes},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume = {29},
  year = 2007,
  number = {12},
  pages = {2247--2253}
}




@inproceedings {nayak_vhci2005,
author= {S. Nayak and S. Sarkar and B. Loeding},
title= {Unsupervised Modeling of Signs Embedded in Continuous Sentences},
booktitle= {IEEE Workshop on Vision for Human-Computer Interaction},
year= 2005
}




% model based, multiple examples (60 per action)
@inproceedings{ke_iccv2005,
 author = {Y. Ke and R. Sukthankar and M. Hebert},
 title = {Efficient Visual Event Detection Using Volumetric Features},
 booktitle = {IEEE International Conference on Computer Vision (ICCV)},
 volume = {1},
 year = {2005},
 pages = {166--173}
 }


% same as previous stuff, boston-104 dataset, uses stereo
@inproceedings {dreuw_ibpria2009,
author= {Dreuw, P. and Steingrube, P. and Deselaers, T. and Ney, H.},
title= {Smoothed Disparity Maps for Continuous American Sign Language Recognition},
booktitle= {Iberian Conference on Pattern Recognition and Image Analysis},
year= 2009,
pages= {24-31}
}


% again hmms, specifies that some signs only appeared once in the
% training set.
@InProceedings {dreuw_itg2008,
author= {Dreuw, P. and Ney, H.},
title= {Visual Modeling and Feature Adaptation in Sign Language Recognition},
booktitle= {ITG Conference on Speech Communication},
year= 2008
}


% uses hmms, based on trigrams and phonemes. 104 unique words
@InProceedings {dreuw_fg2008,
author= {Dreuw, P. and Forster, J. and Deselaers, T. and Ney, H.},
title= {Efficient Approximations to Model-based Joint Tracking and Recognition of Continuous Sign Language},
booktitle= {IEEE International Conference Automatic Face and Gesture Recognition},
year= 2008
}




% here they specify that they use a 3-state model, with 3 gaussian
% mixtures per state, and a global covariance matrix.
@inproceedings {dreuw_interspeech2007,
author= {Dreuw, P. and Rybach, D. and Deselaers, T. and Zahedi, M. and Ney, H.},
title= {Speech Recognition Techniques for a Sign Language Recognition System},
booktitle= {Interspeech},
year= 2007,
pages= {2513-2516}
}




% uses hmms, multiple examples per sign, not a competitor,
% max  vocabulary is 35 gestures.
@inproceedings {dreuw_smvp2006,
author= {Dreuw, P. and Deselaers, T. and Keysers, D. and Ney, H.},
title= {Modeling Image Variability in Appearance-Based Gesture Recognition},
booktitle= {ECCV Workshop on Statistical Methods in Multi-Image and Video Processing},
year= 2006,
pages= {7-18}
}




@inproceedings{farhadi_cvpr2007,
  author    = {A. Farhadi and
               D. A. Forsyth and
               R. White},
  title     = {Transfer Learning in Sign language},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2007}
}




@inproceedings{cooper_cvpr2009,
  author    = {H. Cooper and
               R. Bowden},
  title     = {Learning signs from subtitles: A weakly supervised approach
               to sign language recognition},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2009},
  pages     = {2568-2574}
}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% end of references for ECCV 2010 paper on
% the ASL sign look up project
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% start of references for 2010 NSF CAREER proposal
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


@inproceedings{sudderth_cvpr2003,
  author    = {E. Sudderth and
               A. Ihler and
               W. Freeman and
               A. Willsky},
  title     = {Nonparametric Belief Propagation},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2003},
  volume = {1},
  pages     = {605-612}
}




@inproceedings{sudderth_nips2004,
  author    = {E. Sudderth and
               M. Mandel and
               W. Freeman and
               A. Willsky},
  title     = {Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation},
  booktitle = {Neural Information Processing Systems (NIPS)},
  year      = {2004}
}




@inproceedings{coughlan_eccv2002,
 author = {J. M. Coughlan and S. J. Ferreira},
 title = {Finding Deformable Shapes Using Loopy Belief Propagation},
 booktitle = "European Conference on Computer Vision (ECCV)",
 year = {2002},
 volume = {3},
 pages = {453-468}
 }




@inproceedings{sigal_nips2003,
  author = " L. Sigal and M. Isard and B. H. Sigelman and M. J. Black",
  title = " Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation",
  booktitle = {Neural Information Processing Systems (NIPS)},
  volume = {16},
  pages = "1539-1546",
  year = "2003"
  }




@inproceedings{zhang_cvpr2004,
  author    = {J. Zhang and
               R. Collins and
               Y. Liu},
  title     = {Representation and Matching of Articulated Shapes},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  address   = {Washington D.C.},
  year      = {2004},
  volume    = {2},
  pages     = {342-349}
}




@inproceedings {kahol_fg2004,
author = { Kahol, K.  and  Tripathi, P.  and  Panchanathan, S.},
title = {Automated Gesture Segmentation From Dance Sequences},
year = {2004},
        pages     = {883-888},
  BOOKTITLE = {Automatic Face and Gesture Recognition}
}




@article{yang_pami2009,
        AUTHOR = "Yang, H. D. and Sclaroff, S. and Lee, S. W.",
        TITLE = "Sign Language Spotting with a Threshold Model Based on Conditional
Random Fields",
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
        VOLUME = "31",
        YEAR = "2009",
        NUMBER = "7",
        MONTH = "July",
        PAGES = "1264-1277"
}


@inproceedings{das_pkdd1997,
  author    = {G. Das and
               D. Gunopulos and
               H. Mannila},
  title     = {Finding Similar Time Series},
  booktitle = {Principles of Data Mining and Knowledge Discovery (PKDD)},
  year      = {1997},
  pages     = {88-100}
}




@article{marteau_pami2009,
  author    = {P.-F. Marteau},
  title     = {Time Warp Edit Distance with Stiffness Adjustment for Time
               Series Matching},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume    = {31},
  number    = {2},
  year      = {2009},
  pages     = {306-318}
}




@inproceedings{felzenszwalb_cvpr2007,
  author    = {P. F. Felzenszwalb and
               J. D. Schwartz},
  title     = {Hierarchical Matching of Deformable Shapes},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2007}
}




@inproceedings{sigal_cvpr2004,
  author    = {L. Sigal and
               S. Bhatia and
               S. Roth and
               M. J. Black and
               M. Isard},
  title     = {Tracking Loose-Limbed People},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2004},
  pages     = {421-428}
}




@inproceedings{blake_nips1996,
  author    = {A. Blake and
               M. Isard},
  title     = {The {CONDENSATION} Algorithm - Conditional Density Propagation
               and Applications to Visual Tracking},
  booktitle = {Neural Information Processing Systems (NIPS)},
  year      = {1996},
  pages     = {361-367}
}




@inproceedings{maccormick_eccv2000,
  author    = {J. MacCormick and
               M. Isard},
  title     = {Partitioned Sampling, Articulated Objects, and Interface-Quality
               Hand Tracking},
  booktitle = "European Conference on Computer Vision (ECCV)",
  volume = {2},
  year      = {2000},
  pages     = {3-19}
}




@article{lee_pami2009,
  author    = {M. W. Lee and
               R. Nevatia},
  title     = {Human Pose Tracking in Monocular Sequence Using Multilevel
               Structured Models},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume    = {31},
  number    = {1},
  year      = {2009},
  pages     = {27-38}
}




@InProceedings{ferrari_cvpr2008,
   author = "Ferrari, V. and Marin-Jimenez, M. and Zisserman, A.",
   year = "2008",
   title = "Progressive Search Space Reduction for Human Pose Estimation",
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}
}




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% end of references for 2010 NSF CAREER proposal
%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% start of references for 2010 NSF CRI proposal
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%




@inproceedings{ramanan_nips2006,
  author    = {D. Ramanan},
  title     = {Learning to parse images of articulated bodies},
  booktitle = {Neural Information Processing Systems (NIPS)},
  year      = {2006},
  pages     = {1129-1136}
}




@article{huenerfauth_ijsc2008,
  author    = {M. Huenerfauth},
  title     = {Spatial, Temporal, and Semantic Models for American Sign
               Language Generation: Implications for Gesture Generation},
  journal   = {International Journal of Semantic Computing},
  volume    = {2},
  number    = {1},
  year      = {2008},
  pages     = {21-45}
}




@inproceedings{breuer_mirage2007,
  author    = {P. Breuer and
               C. Eckes and
               S. M{\"u}ller},
  title     = {Hand Gesture Recognition with a Novel IR Time-of-Flight
               Range Camera-A Pilot Study},
  booktitle = {Conference on Computer Vision/Computer Graphics Collaboration Techniques},
  year      = {2007},
  pages     = {247-260}
}




@inproceedings{romero_icra2010,
  author    = {J. Romero and H. Kjellstr{\"o}m and D. Kragic},
  title     = {Hands in action: Real-time 3D reconstruction of hands in interaction with objects},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year      = {2010}
}




@inproceedings{delagorce_cvpr2008,
  author    = {M. de La Gorce and
               N. Paragios and
               D. J. Fleet},
  title     = {Model-based hand tracking with texture, shading and self-occlusions},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2008}
}




@article{bray_cviu2007,
  author    = {M. Bray and
               E. Koller-Meier and
               L. J. Van Gool},
  title     = {Smart particle filtering for high-dimensional tracking},
  journal   = {Computer Vision and Image Understanding (CVIU)},
  volume    = {106},
  number    = {1},
  year      = {2007},
  pages     = {116-129}
}




@inproceedings{liu_fg2004,
  author    = {X. Liu and
               K. Fujimura},
  title     = {Hand Gesture Recognition using Depth Data},
  BOOKTITLE = "Automatic Face and Gesture Recognition",
  year      = {2004},
  pages     = {529-534}
}




@article{erol_cviu2007,
  author    = {A. Erol and
               G. Bebis and
               M. Nicolescu and
               R. D. Boyle and
               X. Twombly},
  title     = {Vision-based hand pose estimation: A review},
  journal   = {Computer Vision and Image Understanding (CVIU)},
  volume    = {108},
  number    = {1-2},
  year      = {2007},
  pages     = {52-73}
}




@article{usabiaga_mva2009,
  author    = {J. Usabiaga and
               A. Erol and
               G. Bebis and
               R. Boyle and
               X. Twombly},
  title     = {Global hand pose estimation by multiple camera ellipse tracking},
  journal   = {Machine Vision and Applications},
  volume    = {21},
  number    = {1},
  year      = {2009},
  pages     = {1-15}
}




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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% end of references for 2010 NSF CRI proposal
%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% start of references for KAIS 2010 revision 1
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%




@inproceedings{zheng_sigir2007,
  author    = {Z. Zheng and
               K. Chen and
               G. Sun and
               H. Zha},
  title     = {A regression framework for learning ranking functions using
               relative relevance judgments},
  booktitle = {ACM SIGIR Conference on Research and Development in Information (SIGIR)},
  year      = {2007},
  pages     = {287-294}
}




@inproceedings{joachims_kdd2002,
 author = {Joachims, Thorsten},
 title = {Optimizing search engines using clickthrough data},
 booktitle = "{ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining (KDD)",
 year = {2002},
 pages = {133--142}
}


@article {becchetti_kais_online,
   author = {Becchetti, L. and Colesanti, U. and Marchetti-Spaccamela, A. and Vitaletti, A.},
   title = {Recommending items in pervasive scenarios: models and experimental analysis},
   journal = {Knowledge and Information Systems (KAIS)},
   publisher = {Springer London},
   volume = {(published online)},
   url = {http://dx.doi.org/10.1007/s10115-010-0338-4},
   year = {2010}
}




@article {bezerra_kais_online,
   author = {Bezerra, B. L. D. and Carvalho, F. A. T.},
   title = {Symbolic data analysis tools for recommendation systems},
   journal = {Knowledge and Information Systems (KAIS)},
   publisher = {Springer London},
   volume = {(published online)},
   url = {http://dx.doi.org/10.1007/s10115-009-0282-3},
   year = {2010}
}




@article {zhang_kais_online,
   author = {Zhang, R. and Tran, T.},
   title = {An information gain-based approach for recommending useful product reviews},
   journal = {Knowledge and Information Systems (KAIS)},
   publisher = {Springer London},
   volume = {(published online)},
   url = {http://dx.doi.org/10.1007/s10115-010-0287-y},
   year = {2010}
}




@article {kim_kais_online,
   author = {Kim, Y. and Chung, C.-W. and Lee, S.-L. and Kim, D.-H.},
   title = {Distance approximation techniques to reduce the dimensionality for multimedia databases},
   journal = {Knowledge and Information Systems (KAIS)},
   publisher = {Springer London},
   volume = {(published online)},
   url = {http://dx.doi.org/10.1007/s10115-010-0322-z},
   year = {2010}
}




@article {huang_kais_online,
   author = {Huang, K. and Ying, Y. and Campbell, C.},
   title = {Generalized sparse metric learning with relative comparisons},
   journal = {Knowledge and Information Systems (KAIS)},
   publisher = {Springer London},
   url = {http://dx.doi.org/10.1007/s10115-010-0313-0},
   volume = {(published online)},
   year = {2010}
}




@article {chen_kais_online,
   author = {Chen, H. and Liu, J. and Furuse, K. and Yu, J. and Ohbo, N.},
   title = {Indexing expensive functions for efficient multi-dimensional similarity search},
   journal = {Knowledge and Information Systems (KAIS)},
   publisher = {Springer London},
   url = {http://dx.doi.org/10.1007/s10115-010-0303-2},
   volume = {(published online)},
   year = {2010}
}




@article {aronovich_kais2010,
   author = {Aronovich, L. and Spiegler, I.},
   title = {Bulk construction of dynamic clustered metric trees},
   journal = {Knowledge and Information Systems (KAIS)},
   publisher = {Springer London},
   pages = {211-244},
   volume = {22},
   number = {2},
   year = {2010}
}




@article {zhangming_kais2010,
   author = {Zhang, Ming and Alhajj, Reda},
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% This file was created with JabRef 2.4.2.
% Encoding: ISO8859_1


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%
% start of references for NSF CRI 2011 with Gian Luca
%
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  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
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@inproceedings{shotton_cvpr2011,
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  year      = {2011},
  pages     = {1297-1304}
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@article{vlasic_tog2008,
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@article{corazza_abe2006,
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@inproceedings{balan_cvpr2007,
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               L. Sigal and
               M. J. Black and
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               H. W. Haussecker},
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  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2007}
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@inproceedings{guan_iccv2009,
  author    = {P. Guan and
               A. Weiss and
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  booktitle = {IEEE International Conference on Computer Vision (ICCV)},
  year      = {2009},
  pages     = {1381-1388}
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@article{sigal_ijcv2010,
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               A. O. Balan and
               M. J. Black},
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  journal   = {International Journal of Computer Vision (IJCV)},
  volume    = {87},
  number    = {1-2},
  year      = {2010},
  pages     = {4-27}
}




@inproceedings{sigal_eccv2010,
  author    = {L. Sigal and
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               M. Livne},
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  booktitle = {ECCV},
  year      = {2010},
  volume    = {3},
  pages     = {243-257}
}




@article {gall_ijcv2010,
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   volume = {87},
   number = {1},
   year = {2010}
}




@inproceedings{gall_cvpr2009,
  author    = {J. Gall and
               C. Stoll and
               E. de Aguiar and
               C. Theobalt and
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               H.-P. Seidel},
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  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2009},
  pages     = {1746-1753}
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@inproceedings{kjellstrom_cvpr2010,
  author    = {H. Kjellstr{\"o}m and
               D. Kragic and
               M. J. Black},
  title     = {Tracking people interacting with objects},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2010},
  pages     = {747-754}
}




@inproceedings{gall_eccv2010,
  author    = {J. Gall and
               A. Yao and
               L. J. Van Gool},
  title     = {2D Action Recognition Serves 3D Human Pose Estimation},
  booktitle = "European Conference on Computer Vision (ECCV)",
  year      = {2010},
  volume    = {3},
  pages     = {425-438}
}




@article{darby_pr2010,
  author    = {J. Darby and
               B. Li and
               N. Costen},
  title     = {Tracking human pose with multiple activity models},
  journal   = {Pattern Recognition},
  volume    = {43},
  number    = {9},
  year      = {2010},
  pages     = {3042-3058}
}




@article{chen_ivc2010,
  author    = {C. Chen and
               Y. Zhuang and
               J. Xiao},
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  journal   = {Image and Vision Computing},
  volume    = {28},
  number    = {4},
  year      = {2010},
  pages     = {654-667}
}




@inproceedings{andriluka_cvpr2010,
  author    = {M. Andriluka and
               S. Roth and
               B. Schiele},
  title     = {Monocular {3D} pose estimation and tracking by detection},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2010},
  pages     = {623-630}
}




@article{brubaker_hai2010,
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  title     = {Video-based people tracking},
  journal   = {Handbook of Ambient Intelligence and Smart Environments},
  year      = {2010},
  pages     = {57}
}




@article{wang_ijcv2010,
  author    = {C.-W. Wang and
               A. Hunter},
  title     = {Robust Pose Recognition of the Obscured Human Body},
  journal   = {International Journal of Computer Vision (IJCV)},
  volume    = {90},
  number    = {3},
  year      = {2010},
  pages     = {313-330}
}




@article{fossati_pami2010,
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               M. Dimitrijevic and
               V. Lepetit and
               P. Fua},
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  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume    = {32},
  number    = {7},
  year      = {2010},
  pages     = {1165-1181}
}




@inproceedings{park_isvc2010,
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 pages = {726--735}
}




@article{rosales_ijcv2006,
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               S. Sclaroff},
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  journal   = {International Journal of Computer Vision (IJCV)},
  volume    = {67},
  number    = {3},
  year      = {2006},
  pages     = {251-276}
}




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%
% end of references for NSF CRI 2011 with Gian Luca
%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% start of references for GEGR DARPA proposal
%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%




@inproceedings{schindler_cvpr2007,
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@inproceedings{irschara_cvpr2009,
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@article {baatz_ijcv2011,
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   year  = {2011}
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@inproceedings{baatz_eccv2010,
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  booktitle = "European Conference on Computer Vision (ECCV)",
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   year = {2010}
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@article{ni_pami2009,
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  volume    = {31},
  number    = {12},
  year      = {2009},
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@inproceedings{li_eccv2010,
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  year      = {2010},
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@inproceedings{hays_cvpr2008,
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@inproceedings{kalogerakis_iccv2009,
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@article{oliva_pgr2006,
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@inproceedings{agarwal_iccv2009,
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@article {jegou_ijcv2010,
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@inproceedings{chum_iccv2007,
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@inproceedings{chum_cvpr2011,
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@inproceedings{sivic_iccv2003,
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@inproceedings{nister_cvpr2006,
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  year      = {2006},
  pages     = {2161-2168}
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@inproceedings{jain_cvpr2008,
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  year      = {2008}
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@article{kulis_pami2009,
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               P. Jain and
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  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume    = {31},
  number    = {12},
  year      = {2009},
  pages     = {2143-2157}
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@article{ling_pami2007,
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               David W. Jacobs},
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  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume    = {29},
  number    = {2},
  year      = {2007},
  pages     = {286-299}
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@article{bai_pami2010,
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               L. J. Latecki and
               W. Liu and
               Z. Tu},
  title     = {Learning Context-Sensitive Shape Similarity by Graph Transduction},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume    = {32},
  number    = {5},
  year      = {2010},
  pages     = {861-874}
}




@article{lowe_ijcv2004,
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  volume    = {60},
  number    = {2},
  year      = {2004},
  pages     = {91-110}
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@inproceedings{lian_icsm2010,
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  year      = {2010},
  pages     = {25-36}
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@article{tung_ijsm2005,
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  number    = {1},
  year      = {2005},
  pages     = {91-120}
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@inproceedings{sundar_icsm2003,
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               D. Silver and
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               S. J. Dickinson},
  title     = {Skeleton Based Shape Matching and Retrieval},
  booktitle = {Shape Modeling International},
  year      = {2003},
  pages     = {130-142}
}




@article {papadakis_ijcv2010,
   author = {Papadakis, P. and Pratikakis, I. and Theoharis, T. and Perantonis, S.},
   title = {{PANORAMA}: A 3D Shape Descriptor Based on Panoramic Views for Unsupervised 3D Object Retrieval},
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   pages = {177-192},
   volume = {89},
   issue = {2},
   year = {2010}
}




@article{osada_tog2002,
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@article{bronstein_tog2011,
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  journal   = {ACM Transactions on Graphics},
  volume    = {30},
  number    = {1},
  year      = {2011}
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@article{akgul_pami2009,
  author    = {C. B. Akg{\"u}l and
               B. Sankur and
               Y. Yemez and
               F. Schmitt},
  title     = {3D Model Retrieval Using Probability Density-Based Shape Descriptors},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)},
  volume    = {31},
  number    = {6},
  year      = {2009},
  pages     = {1117-1133}
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@article{kernel15,
  author    = {Y. Kong and B. Satarboroujeni and Y. Fu},
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  year      = {2015}
  }



@article{siamese15,
  author    = {S. Berlemont and G. Lefebvre and S. Duffner and C. Garcia},
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  year      = {2015}
  }


@article{pavlo15,
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  year      = {2015}
  }

@article{random15,
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  year      = {2015}
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@article{drive,
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@article{spherical,
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  title     = {Spherical Wavelet Descriptors for Content-based 3D Model Retrieval},
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  year      = {2006},
  pages     = {15}
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%
% end of references for GEGR DARPA proposal
%
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  author = {Y. Xiao and Z. Zhang and A. Beck and J. Yuan and D. Thalmann},
  title = {Human-Robot Interaction by Understanding Upper Body Gestures},
  journal = {Presence},
  year = {2014},
  volume = {23},
  pages = {133 -- 154},
  number = {2}
  }


@incollection{PengWang2015,
year={2015},
isbn={978-3-319-16177-8},
booktitle={Computer Vision - ECCV 2014 Workshops},
volume={8925},
series={Lecture Notes in Computer Science},
editor={Agapito, Lourdes and Bronstein, Michael M. and Rother, Carsten},
doi={10.1007/978-3-319-16178-5_36},
title={Action and Gesture Temporal Spotting with Super Vector Representation},
url={http://dx.doi.org/10.1007/978-3-319-16178-5_36},
publisher={Springer International Publishing},
keywords={Action recognition; Gesture recognition; Temporal spotting; Super vector},
author={Peng, X. and Wang, L. and Cai, Z. and Qiao, Y.},
pages={518-527},
language={English}
}

@ARTICLE{Yang14,
  author = {X. Yang and Y. Tian},
  title = {Action Recognition Using Super Sparse Coding Vector with Spatio-Temporal Awareness},
  journal = {ECCV},
  year = {2014}
  }

@INPROCEEDINGS{Wang2013,
  author={H. Wang and C. Schmid},
  title={Action Recognition with Improved Trajectories},
  booktitle= {IEEE International Conference on Computer Vision},
  year={2013}
}

@ARTICLE{Tian14,
  author = {X. Yang and Y. Tian},
  title = {Super Normal Vector for Activity Recognition Using Depth Sequences},
  journal = {CVPR},
  year = {2014}
  }

 @inproceedings{baraldi2014_379,
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booktitle = {Proc. of 10th IEEE Embedded Vision Workshop (EVW)},
volume = {},
number = {},
year = 2014,
month = jun,
pages = {},
address = {Columbus, Ohio},
}

@inproceedings{gathering,
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 series = {FGIT '09},
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 isbn = {978-3-642-10508-1},
 pages = {78--86},
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}


@ARTICLE{omae13,
  author = {O. Oreifej and Z. Liu},
  title = {{HON4D}: Histogram of Oriented {4D} Normals for Activity Recognition from Depth Sequences},
  journal = {CVPR},
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  pages = {716 -- 723}
  }


@ARTICLE{Luo14,
  author = {J. Luo and W. Wang and H. Qi},
  title = {Spatio-temporal feature extraction and representation for {RGB-D} human action recognition},
  journal = {PRL},
  year = {2014}
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@ARTICLE{Wanqing00,
  author = {W. Li and Z. Zhang and Z. Liu},
  title = {Action recognition based on a bag of {3D} points},
  journal = {CVPR workshops},
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  pages = {9 -- 14}
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@ARTICLE{gang14,
  author = {G. Yu and Z. Liu and J. Yuan},
  title = {Discriminative Orderlet Mining For Real-time  Recognition of Human-Object Interaction},
  journal = {ACCV},
  year = {2014}
  }




@ARTICLE{Derpanis13,
  author = {KG Derpanis and M Sizintsev and KJ Cannons and RP Wildes},
  title = {Action spotting and recognition based on a spatiotemporal orientation analysis},
  journal = {IEEE TPAMI},
  year = {2013},
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  pages = {527 -- 540},
  number = {3}
  }


@ARTICLE{Junsong11,
  author = {J. Yuan and Z. Liu and Y. Wu},
  title = {Discriminative Video Pattern Search for Efficient Action
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  journal = {IEEE TPAMI},
  year = {2011},
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@ARTICLE{Hui14,
  author = {H. Liang and J. Yuan and D. Thalmann},
  title = {Parsing the Hand in Depth Images},
  journal = {IEEE Transactions on Multimedia},
  year = {2014},
  volume = {16},
  pages = {1241--1253},
  number = {5}
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@ARTICLE{NeverovaWolf14,
  author = {N. Neverova and C. Wolf and G. W. Taylor and F. Nebout},
  title = {Hand segmentation with structured convolutional learning},
  journal = {ACCV},
  year = {2014}
  }



@ARTICLE{Zhou13,
  author = {Z. Ren and J. Yuan and J. Meng and Z. Zhang},
  title = {Robust Part-Based Hand Gesture Recognition Using {Kinect} Sensor},
  journal = {IEEE Transactions on Multimedia},
  year = {2013},
  volume = {15},
  pages = {1110--1120},
  number = {5}
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@ARTICLE{ChengLi2013,
  author = {C. Li and K. M. Kitani},
  title = {Pixel-level Hand Detection for Ego-centric Videos},
  journal = {CVPR},
  year = {2013}
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@ARTICLE{Hui2014,
  author = {H. Liang and J. Yuan and D. Thalmann and Z. Zhang},
  title = {Model-based hand pose estimation via spatial-temporal hand parsing and {3D} fingertip localization},
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  }


%%%%%%%%%%%%%%%%%%%%
%%
%% Added by Vassilis, October 2015
%%
%%%%%%%%%%%%%%%%%%%%


@inproceedings{wang_fg2015,
AUTHOR = "H. Wang and X. Chai and Y. Zhou and X. Chen",
TITLE = "Fast sign language recognition benefited from low rank approximation",
BOOKTITLE = "Automatic Face and Gesture Recognition",
YEAR="2015"
}


@inproceedings{conly_petra2015,
  author    = {C. Conly and Z. Zhang and  V. Athitsos},
  title     = {An Integrated {RGB-D} System for Looking Up the Meaning of Signs},
  booktitle = {Pervasive Technologies Related to Assistive Environments (PETRA)},
  year      = {2015}
 }

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Added by Vassilis, January 2015
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@inproceedings{pieropan_iros2014,
title = {Audio-visual classification and detection of human manipulation actions},
author = {A. Pieropan and G. Salvi and K.Pauwels and H. Kjellström},
year = {2014},
booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
keywords = {}
}


@inproceedings{czabke_pcth2010,
  author    = {A. Czabke and
               J. Neuhauser and 
               T. C. Lueth},
  title     = {Recognition of interactions with objects based on radio modules},
  booktitle = {International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth)},
  year      = {2010}
  }


@inproceedings{shapovalova_pria2011,
  author    = {N. Shapovalova and 
               W. Gong. and 
               M. Pedersoli and
               F. X. Roca
               and J. Gonzalez},
  title     = {On importance of interactions and context in human action recognition},
  booktitle = {Pattern Recognition and Image Analysis},
  pages     = {58--66},
  year      = {2011}
  }
  
  
  @inproceedings{fathi_cvpr2011,
  author    = {A. Fathi and
               X. Ren and
               J.M. Rehg},
  title     = {Learning to recognize objects in egocentric activities},
  booktitle = {{IEEE} Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages = {3281--3288}
  year      = {2011}
  }


