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Hand Gesture Spotting Based on 3D Dynamic Features Using Hidden Markov Models

  • Conference paper
Signal Processing, Image Processing and Pattern Recognition (SIP 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 61))

Abstract

In this paper, we propose an automatic system that handles hand gesture spotting and recognition simultaneously in stereo color image sequences without any time delay based on Hidden Markov Models (HMMs). Color and 3D depth map are used to segment hand regions. The hand trajectory will determine in further step using Mean-shift algorithm and Kalman filter to generate 3D dynamic features. Furthermore, k-means clustering algorithm is employed for the HMMs codewords. To spot meaningful gestures accurately, a non-gesture model is proposed, which provides confidence limit for the calculated likelihood by other gesture models. The confidence measures are used as an adaptive threshold for spotting meaningful gestures. Experimental results show that the proposed system can successfully recognize isolated gestures with 98.33% and meaningful gestures with 94.35% reliability for numbers (0-9).

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Author information

Authors and Affiliations

  1. Institute for Electronics, Signal Processing and Communications, Otto-von-Guericke-University, Magdeburg, Germany

    Mahmoud Elmezain, Ayoub Al-Hamadi & Bernd Michaelis

Authors
  1. Mahmoud Elmezain
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  2. Ayoub Al-Hamadi
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  3. Bernd Michaelis
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Editor information

Editors and Affiliations

  1. University of Warsaw and Infobright Inc., Poland

    Dominik Ślęzak

  2. Indian Statistical Institute, India

    Sankar K. Pal

  3. University of Tasmania, 7001, Hobart, Australia

    Byeong-Ho Kang

  4. Lab. of Multimedia Information Technology (MMIT), East China Normal University (ECNU), P.O. Box, 200062, Shanghai, China

    Junzhong Gu

  5. Nagasaki University, Japan

    Hideo Kuroda

  6. Hannam University, 306-791, Daejeon, South Korea

    Tai-hoon Kim

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© 2009 Springer-Verlag Berlin Heidelberg

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Elmezain, M., Al-Hamadi, A., Michaelis, B. (2009). Hand Gesture Spotting Based on 3D Dynamic Features Using Hidden Markov Models. In: Ślęzak, D., Pal, S.K., Kang, BH., Gu, J., Kuroda, H., Kim, Th. (eds) Signal Processing, Image Processing and Pattern Recognition. SIP 2009. Communications in Computer and Information Science, vol 61. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10546-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-10546-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10545-6

  • Online ISBN: 978-3-642-10546-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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