• DocumentCode
    170272
  • Title

    Hand gesture recognition based on depth map

  • Author

    Sykora, Petr ; Kamencay, Patrik ; Zachariasova, Martina ; Hudec, Robert

  • Author_Institution
    Dept. of telecommunicat ions & multimedia, Univ. of Zilina, Zilina, Slovakia
  • fYear
    2014
  • fDate
    19-20 May 2014
  • Firstpage
    109
  • Lastpage
    112
  • Abstract
    In this paper a proposed method for gesture recognition using depth map image is presented. Three different feature extraction methods are presented too. All of them are based on Radon transform. First method reduces the feature vector of Radon transform by averaging its values. Next approach uses discrete cosine transform on radon graph, thus the energy of graph is reorganized. This approach concentrates the energy of graph to upper left corner and the rest can be cutoff with minimal error. Last approach applies R transform on radon graph, those create 1D shape-curve in specific direction. For the classification of features vectors, the support vector machine is used. Finally, the experimental results of all descriptors are shown.
  • Keywords
    Radon transforms; discrete cosine transforms; feature extraction; gesture recognition; graph theory; image classification; palmprint recognition; support vector machines; ID shape-curve; R transform; Radon transform; depth map image; discrete cosine transform; feature extraction method; feature vector classification; hand gesture recognition; radon graph; support vector machine; Accuracy; Image recognition; Image segmentation; Real-time systems; Sensors; Support vector machine classification; Transforms; DCT; depth map; discrete cosine transform; gesture recognition; radon transform; support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ELEKTRO, 2014
  • Conference_Location
    Rajecke Teplice
  • Print_ISBN
    978-1-4799-3720-2
  • Type

    conf

  • DOI
    10.1109/ELEKTRO.2014.6847882
  • Filename
    6847882