Belief Theory-Based Classifiers Comparison for Static Human Body Postures Recognition in Video
This paper presents various classifiers results from a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The three classifiers considered are a naïve one and two based on the belief theory. The belief theory-based classifiers use either a classic or restricted plausibility criterion to make a decision after data fusion. The data come from the people 2D segmentation and from their face localization. Measurements consist in distances relative to a reference posture. The efficiency and the limits of the different classifiers on the recognition system are highlighted thanks to the analysis of a great number of results. This system allows real-time processing.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1331173Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1173
 URL of the website of the SIMILAR European Network of Excellence, "http://www.similar.cc/," .
 J. K. Aggarwal and Q. Cai, "Human motion analysis: A review," Computer Vision and Image Understanding, vol. 73, no. 3, pp. 428-440, 1999.
 J. J. Wang and S. Singh, "Video analysis of human dynamics- a survey," Real-Time Imaging, vol. 9, pp. 321-346, 2003.
 L. Wang, W. Hu, and T. Tan, "Recent developments in human motion analysis," Pattern Recognition, vol. 36, no. 3, pp. 585-601, 2003.
 C. W. Sul, K. C. Lee, and K. Wohn, "Virtual stage: a location-based karaoke system," IEEE Multimedia, vol. 5, no. 2, pp. 42-52, 1998.
 M. Oren, C. Papageorgiou, P. Sinha, E. Osuna, and T. Poggio, "Pedestrian detection using wavelet templates," in Computer Vision and Pattern Recognition, 1997, pp. 193-199.
 I. Haritaoglu, D. Harwood, and L. Davis, "Ghost: A human body part labeling system using silhouettes," in International Conference on Computer Vision and Pattern Recognition, 1998, pp. 77-82.
 L. Campbell and A. Bobick, "Using phase space constraints to represent human body motion," International Workshop on Automatic Face and Gesture Recognition, 1995.
 G. Shafer, "A mathematical theory of evidence," Princeton University Press, 1976.
 A. Dempster, "A generalization of bayesian inference," Journal of the Royal Statistical Society, vol. 30, pp. 205-245, 1968.
 P. Smets and R. Kennes, "The transferable belief model," Artificial Intelligence, vol. 66, pp. 191-234, 1994.
 P. Smets, "The transferable belief model for quantified belief representation," in Handbook of Defeasible Reasoning and Uncertainty Management Systems, Vol. 1, D. M. Gabbay and P. Smets, Eds., pp. 267-301. Kluwer, Doordrecht, The Netherlands, 1998.
 A. Caplier, L. Bonnaud, and J-M. Chassery, "Robust fast extraction of video objects combining frame differences and adaptative reference image," in IEEE International Conference on Image Processing, September 2001.
 V. Girondel, L. Bonnaud, and A. Caplier, "Hands detection and tracking for interactive multimedia applications," in International Conference on Computer Vision and Graphics, September 2002, pp. 282-287.