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Optical Engineering

Bayesian variational human tracking based on informative body parts
Author(s): Yi Zhou; Shibao Zheng; Hichem Snoussi
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Paper 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.

Paper Details

Date Published: 5 June 2012
PDF: 17 pages
Opt. Eng. 51(6) 067203 doi: 10.1117/1.OE.51.6.067203
Published in: Optical Engineering Volume 51, Issue 6
Show Author Affiliations
Yi Zhou, Shanghai Jiao Tong Univ. (China)
Shibao Zheng, Shanghai Jiao Tong Univ. (China)
Hichem Snoussi, Univ. de Technologie Troyes (France)


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