Object tracking within the framework of concept drift

Authors:
Li Chen;Yue Zhou;Jie Yang
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China,Key Laboratory of System Control and Information Processing, Ministry of Education of China, S ...;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China,Key Laboratory of System Control and Information Processing, Ministry of Education of China, S ...;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China,Key Laboratory of System Control and Information Processing, Ministry of Education of China, S ...
Venue:
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Year:
2012

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Abstract

It is well known that the backgrounds or the targets always change in real scenes, which weakens the effectiveness of classical tracking algorithms because of frequent model mismatches. In this paper, an object tracking algorithm within the framework of concept drift is proposed to solve this problem. We detect the driftpoints using a simple message-passing algorithm based on Bayesian Approach. The analyzed probability distribution lays the foundation for the self-adaption of our new model. Our tracking algorithm within the framework of concept drift improves the tracking robustness and accuracy which is illustrated by the two experiments on two real-world changing scenes.