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Learning of Facial Gestures Using SVMs

  • Conference paper
Next Wave in Robotics (FIRA 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 212))

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Abstract

This paper describes the implementation of a fast and accurate gesture recognition system. Image sequences are used to train a standard SVM to recognize Yes, No, and Neutral gestures from different users. We show that our system is able to detect facial gestures with more than 80% accuracy from even small input images.

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References

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Author information

Authors and Affiliations

  1. Autonomous Agent Lab, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2

    Jacky Baltes, Stela Seo, Chi Tai Cheng, M. C. Lau & John Anderson

Authors
  1. Jacky Baltes
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  2. Stela Seo
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  3. Chi Tai Cheng
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  4. M. C. Lau
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  5. John Anderson
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Tzuu-Hseng S. Li

  2. National Kaohsiung First University of Science and Technology, 2 Juoyue Road, 40227, Taichung, Taiwan

    Kuo-Yang Tu

  3. Department of Electrical Engineering, Nationan Chung Hsing University, No. 250, Kuo-Kuang Road, 40227, Taichung, Taiwan

    Ching-Chih Tsai

  4. Department of Applied Electronics Technology, National Taiwan Normal University, 162 He-Ping East Road, Section 1, 10610, Taipei, Taiwan

    Chen-Chien Hsu

  5. National Kaohsiung First University of Science and Technology, 2 Juoyue Road, Nantsu District, 811, Kaohsiung City, Taiwan

    Chien-Cheng Tseng

  6. National University of Singapore, Singapore

    Prahlad Vadakkepat

  7. Department of Computer Science,, University of Manitoba, R3T 2N2, Winnipeg, Manitoba, Canada

    Jacky Baltes

  8. Department of Computer Science, University of Manitoba, R3T 2N2, Winnipeg, Manitoba, Canada

    John Anderson

  9. Tamkang University, Taipei, Taiwan

    Ching-Chang Wong

  10. Technische Universität Dortmund, Dortmund, Germany

    Norbert Jesse

  11. Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., 106, Taipei, Taiwan

    Chung-Hsien Kuo

  12. Institute of System Information and Control, National Kaohsiung First University of Science and Technology, 2 Juoyue Road, Nantsu District, 811, Kaohsiung City, Taiwan

    Haw-Ching Yang

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© 2011 Springer-Verlag Berlin Heidelberg

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Baltes, J., Seo, S., Cheng, C.T., Lau, M.C., Anderson, J. (2011). Learning of Facial Gestures Using SVMs. In: Li, TH.S., et al. Next Wave in Robotics. FIRA 2011. Communications in Computer and Information Science, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23147-6_18

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  • DOI: https://doi.org/10.1007/978-3-642-23147-6_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23146-9

  • Online ISBN: 978-3-642-23147-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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