Human Action Recognition Based on Spatio-temporal Features

  • Nikhil Sawant
  • K. K. Biswas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5909)

Abstract

This paper studies the technique of human action recognition using spatio-temporal features. We concentrate on the motion and the shape patterns produced by different actions for action recognition. The motion patterns generated by the actions are captured by the optical flows. The Shape information is obtained by Viola-Jones features. Spatial features comprises of motion and shape information from a single frame. Spatio-temporal descriptor patterns are formed to improve the accuracy over spatial features. Adaboost learns and classifies the descriptor patterns. We report the accuracy of our system on a standard Weizmann dataset.

References

  1. 1.
    Gavrila, D.M.: The visual analysis of human movement: a survey. Comput. Vis. Image Underst. 73(1), 82–98 (1999)MATHCrossRefGoogle Scholar
  2. 2.
    Sullivan, J., Carlsson, S.: Recognizing and tracking human action. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 629–644. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Blank, M., Gorelick, L., Shechtman, E., Irani, M., Basri, R.: Actions as space-time shapes. In: ICCV 2005: Proceedings of the Tenth IEEE International Conference on Computer Vision, Washington, DC, USA, pp. 1395–1402. IEEE Computer Society, Los Alamitos (2005)CrossRefGoogle Scholar
  4. 4.
    Niu, F., Abdel-Mottaleb, M.: View-invariant human activity recognition based on shape and motion features, pp. 546–556 (December 2004)Google Scholar
  5. 5.
    Goodhart, T., Yan, P., Shah, M.: Action recognition using spatio-temporal regularity based features, 745–748 (31 2008 - April 4 2008)Google Scholar
  6. 6.
    Danafar, S., Gheissari, N.: Action recognition for surveillance applications using optic flow and SVM. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part II. LNCS, vol. 4844, pp. 457–466. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
    Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision (1981)Google Scholar
  8. 8.
    Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vision 57(2), 137–154 (2004)CrossRefGoogle Scholar
  9. 9.
    Freund, Y., Schapire, R.: A short introduction to boosting. J. Japan. Soc. for Artif. Intel. 14(5), 771–780 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Nikhil Sawant
    • 1
  • K. K. Biswas
    • 1
  1. 1.Dept. of CSEIIT DelhiIndia

Personalised recommendations