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Learning of Facial Gestures Using SVMs

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

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.

Keywords

  • Facial Recognition
  • SVM
  • Machine Learning

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  • DOI: 10.1007/978-3-642-23147-6_18
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References

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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: , 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)