Learning of Facial Gestures Using SVMs

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


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.


Facial Recognition SVM Machine Learning 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Chang, C.-C., Lin, C.-J.: Libsvm: a library for support vector machines. Computer, 1–30 (2001)Google Scholar
  2. 2.
    Hagg, J., Rkl, B., Akan, B., Asplund, L.: Gesture recognition using evolution strategy neural network, pp. 245–248. IEEE, Los Alamitos (2008)Google Scholar
  3. 3.
    Hasanuzzaman, M., Ampornaramveth, V., Bhuiyan, M.A., Shirai, Y., Ueno, H.: Real-time vision-based gesture recognition for human robot interaction. In: 2004 IEEE International Conference on Robotics and Biomimetics, pp. 413–418 (2004)Google Scholar
  4. 4.
    Lee, S.-W.: Automatic gesture recognition for intelligent human-robot interaction. In: 7th International Conference on Automatic Face and Gesture Recognition FGR 2006, pp. 645–650 (2006)Google Scholar
  5. 5.
    Mitra, S., Acharya, T.: Gesture recognition: A survey. IEEE Transactions on Systems Man and Cybernetics Part C Applications and Reviews 37(3), 311–324 (2007)CrossRefGoogle Scholar
  6. 6.
    Oshita, M., Matsunaga, T.: Automatic learning of gesture recognition model using som and svm. Advances in Visual Computing, 751–759 (2010)Google Scholar
  7. 7.
    Valibeik, S., Yang, G.-Z.: Segmentation and Tracking for Vision Based Human Robot Interaction. IEEE, Los Alamitos (2008)CrossRefGoogle Scholar
  8. 8.
    Vapnik, V.N.: An overview of statistical learning theory. IEEE Transactions on Neural Networks 10(5), 988–999 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Autonomous Agent LabUniversity of ManitobaWinnipegCanada

Personalised recommendations