Bayesian variational human tracking based on informative body parts

Yi Zhou; Shibao Zheng; Hichem Snoussi

doi:10.1117/1.OE.51.6.067203

5 June 2012 Bayesian variational human tracking based on informative body parts

Yi Zhou, Shibao Zheng, Hichem Snoussi

Author Affiliations +

Optical Engineering, Vol. 51, Issue 6, 067203 (June 2012). https://doi.org/10.1117/1.OE.51.6.067203

Abstract

The authors propose a fragment-based variational filtering technique for human tracking. Based on human classifiers and histograms of oriented gradients descriptor, more informative local parts of the human body are selected in the reference model and updated during the tracking process. Hyper-parameters of the variational Bayesian filter are adaptively tuned in order to cope with variable scenes and occlusions. To speed up the initialization and reference updating, an efficient motion cue is fused with the human detection. Extensive experimental results on benchmark datasets show that the proposed tracker is effective and robust.

Citation Download Citation

Yi Zhou, Shibao Zheng, and Hichem Snoussi "Bayesian variational human tracking based on informative body parts," Optical Engineering 51(6), 067203 (5 June 2012). https://doi.org/10.1117/1.OE.51.6.067203

Published: 5 June 2012

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