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Hand Gesture Recognition Based on Segmented Singular Value Decomposition

  • Jing Liu
  • Manolya Kavakli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6277)

Abstract

The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSVD) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.

Keywords

Similarity Measure Singular Vector Gesture Recognition Multivariate Time Series Hand Gesture Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jing Liu
    • 1
  • Manolya Kavakli
    • 1
  1. 1.Department of ComputingMacquarie UniversityAustralia

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