VIDEO BASED HUMAN ACTIVITY RECOGNITION USING WAVELET TRANSFORM AND HIDDEN CONDITIONAL RANDOM FIELDS (HCRF)

Muhammad Hameed Siddiqi, La The Vinh, Adil Mehmood Khan

2012

Abstract

In this research, we proposed testing and validating the accuracy of employing wavelet transform and Hidden Conditional Random Field (HRCF) for video based activity recognition. For feature extraction, Symlet wavelet was tested and decomposed up to 4 levels, and some of the highest coefficients were extracted from each level of decomposition. These coefficients were based on the average frequency of each video frame and the time difference between each frame. Finally, a novel HRCF model was applied for recognition. The proposed method was tested on a database of ten activities, where the data were collected from nine different people, and compared with one of the existing techniques. The overall recognition rate, using the symlet wavelet family (Symlet 4), was 93% that showed an improvement of 13% in performance.

References

  1. Aggarwal, J. K., Cai, Q., 1999. Human motion analysis: A review. Comput. Vis. Image Und., vol. 73(3), pp. 428- 40.
  2. Cedras, C., Shah, M., 1995. Motion-based recognition: A survey. Image Vis. Comput., vol. 13(2), pp. 129-55.
  3. Gavrila, D. M., 1999. The visual analysis of human movement: a survey: Comput. Vis. Image Und., vol. 73(1), pp. 82-98.
  4. Gorelick, L., Blank M., Shechtman E., Irani M., Basri R., 2007. Actions as Space-Time Shapes. IEEE Trans. PAMI., vol. 29(12), pp.2247-53.
  5. Gu, T., Wu, Z., Tao, X., Pung, H. K., Lu, J., 2009. epSICAR: An Emerging Patterns based approach to sequential, interleaved and Concurrent Activity Recognition. In Proc. of IEEE Intl. Conference on Pervasive Computing and Communications.
  6. Kim, T.-S., Uddin, M. Z., 2010. Silhouette-based Human Activity Recognition Using Independent Component Analysis, Linear Discriminant Analysis and Hidden Markov Model. New Developments in Biomedical Engineering, ISBN: 978-953-7619-57-2. Edited by: Domenico Campolo. Published by InTech.
  7. Moeslund, T. B., Hilton, A., Kruger, V., 2006. A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Und., vol. 104(2), pp. 90-126.
  8. Siddiqi, M. H., Fahim, M., Lee, S. Y., Lee, Y.-K, 2010. Human Activity Recognition Based on Morphological Dilation followed by Watershed Transformation Method. Proc. of International Conference on Electronics and Information Engineering (ICEIE), pp. V2 433-V2 437.
  9. Turaga, P., Chellappa, R., Subrahmanian, V. S., Udrea, O., 2008. Machine Recognition of Human Activities: A survey. IEEE Trans. Circuits and Systems for VideoTechnology, vol. 18(11), pp. 1473-88.
  10. Turunen, J, 2011. A Wavelet-based Method for Estimating Damping in Power Systems. PhD. Thesis, Aalto University, School of Electrical Engineering, Department of Electrical Engineering Power Transmission Systems.
  11. Uddin, M. Z., Lee, J. J., Kim, T.-S, 2010. Independent shape component-based human activity recognition via Hidden Markov Model. Appl. Intell, vol. 33(2), pp. 193-206.
  12. Uddin, M. Z., Lee, J. J., Kim, T.-S. 2008. Shape-Based Human Activity Recognition Using Independent Component Analysis and Hidden Markov Model. Proc. of 21st International Conference on Industrial, Engineering, and other Applications of Applied Intelligent Systems, pp.245-254.
  13. Yilmaz, A., Javed, O., Shah, M., 2006. Object tracking: A survey. ACM Comput. Surv., vol. 38(4).
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Paper Citation


in Harvard Style

Hameed Siddiqi M., The Vinh L. and Mehmood Khan A. (2012). VIDEO BASED HUMAN ACTIVITY RECOGNITION USING WAVELET TRANSFORM AND HIDDEN CONDITIONAL RANDOM FIELDS (HCRF) . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-03-7, pages 401-404. DOI: 10.5220/0003818704010404


in Bibtex Style

@conference{visapp12,
author={Muhammad Hameed Siddiqi and La The Vinh and Adil Mehmood Khan},
title={VIDEO BASED HUMAN ACTIVITY RECOGNITION USING WAVELET TRANSFORM AND HIDDEN CONDITIONAL RANDOM FIELDS (HCRF)},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={401-404},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003818704010404},
isbn={978-989-8565-03-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)
TI - VIDEO BASED HUMAN ACTIVITY RECOGNITION USING WAVELET TRANSFORM AND HIDDEN CONDITIONAL RANDOM FIELDS (HCRF)
SN - 978-989-8565-03-7
AU - Hameed Siddiqi M.
AU - The Vinh L.
AU - Mehmood Khan A.
PY - 2012
SP - 401
EP - 404
DO - 10.5220/0003818704010404