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A Compound Eigenspace for Recognizing Directed Human Activities

  • Abdunnaser Diaf
  • Boubakeur Boufama
  • Rachid Benlamri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7325)

Abstract

This paper proposes a robust appearance-based method for recognizing directed human activities with scale variation based on a compound eigenspace. The method addresses two main issues associated with activity recognition when a human is moving away from or closer to the cameras. The first issue is the variation in human silhouette sizes as a result of object-camera distance changes. The second is the insufficient information of shape and speed of the limbs due to self occlusions. An eigenvector-based linear algorithm is employed for dimensionality reduction and activity recognition here. In addition to the conventional data available in each video frame, our method extracts two more pieces of information that are used to control the recognition process. In particular, the use of a compound eigenspace, controlled by the silhouette’s relative speed and linear displacement vector, has clearly improved the recognition. The method has been trained and tested using the four scenarios of the KTH dataset, which contains hundreds of videos partitioned into six human activities.

Keywords

Human Activity Recognition Eigenspace Motion Intensity Image 

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References

  1. 1.
    Bobick, A., Davis, J.: The recognition of human movement using temporal templates. IEEE Transactions on PAMI 23(3), 257–267 (2001)CrossRefGoogle Scholar
  2. 2.
    Diaf, A., Benlamri, R., Boufama, B.: An effective view-based motion representation for human motion recognition. In: International Symposium on Modeling and Implementing Complex Systems, pp. 57–64 (May 2010)Google Scholar
  3. 3.
    Diaf, A., Ksantini, R., Boufama, B., Benlamri, R.: A Novel Human Motion Recognition Method Based on Eigenspace. In: Campilho, A., Kamel, M. (eds.) ICIAR 2010. LNCS, vol. 6111, pp. 167–175. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Dornaika, F., Davoine, F.: On appearance based face and facial action tracking. IEEE Transactions on Circuits and Systems for Video Technology 16(9), 1107–1124 (2006)CrossRefGoogle Scholar
  5. 5.
    Fukunaga, K.: Introduction to statistical pattern recognition, 2nd edn. Academic Press Professional, Inc., San Diego (1990)zbMATHGoogle Scholar
  6. 6.
    Jolliffe, I.T.: Principal Component Analysis. Springer (1986)Google Scholar
  7. 7.
    Lehmann, T., Gonner, C., Spitzer, K.: Survey: interpolation methods in medical image processing. IEEE Transactions on Medical Imaging 18(11), 1049–1075 (1999)CrossRefGoogle Scholar
  8. 8.
    Meng, H., Freeman, M., Pears, N., Bailey, C.: Real-time human action recognition on an embedded, reconfigurable video processing architecture. Journal of Real-Time Image Processing 3(3), 163–176 (2008)CrossRefGoogle Scholar
  9. 9.
    Moeslund, T., Hilton, A., Kruger, V.: A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding 104(2), 90–126 (2006)CrossRefGoogle Scholar
  10. 10.
    Ogata, T., Tan, J., Ishikawa, S.: High-speed human motion recognition based on a motion history image and an eigenspace. IEICE - Transactions on Information and Systems E89-D(1), 281–289 (2006)CrossRefGoogle Scholar
  11. 11.
    Rahman, M., Ishikawa, S.: Human motion recognition using an eigenspace. Pattern Recognition Letters 26, 687–697 (2005)CrossRefGoogle Scholar
  12. 12.
    Schuldt, C., Laptev, I., Caputo, B.: Recognizing human actions: A local svm approach. In: The 17th ICPR, vol. 3, pp. 32–36 (2004)Google Scholar
  13. 13.
    Zivkovic, Z.: Improved adaptive gaussian mixture model for background subtraction. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 2, pp. 28–31 (August 2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Abdunnaser Diaf
    • 1
  • Boubakeur Boufama
    • 1
  • Rachid Benlamri
    • 2
  1. 1.University of WindsorWindsorCanada
  2. 2.Lakehead UniversityThunder BayCanada

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