Robust object tracking algorithm in natural environments

Authors:
Shi-qiang Hu;Guo-zhuang Liang;Zhong-liang Jing
Affiliations:
College of Informatics and Electronics, Hebei University of Science and Technology, Shijiazhuang, China;College of Informatics and Electronics, Hebei University of Science and Technology, Shijiazhuang, China;Institute of Informatics and Electronics, Shanghai Jiaotong University, Shanghai, China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
Year:
2006

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Abstract

In order to realize robust visual tracking in natural environments, a novel algorithm based on adaptive appearance model is proposed. The model can adapt to changes in object appearance over time. A mixture of three Gaussian distributions models the value of each pixel. An online Expectation Maximization (EM) algorithm is developed to update the parameters of the Gaussians. The observation model in the particle filter is designed based on the adaptive appearance model. Numerous experimental results demonstrate that our proposed algorithm can track objects well under illumination change, large pose variation, and partial or full occlusion.