Building a Robust Appearance Model for Object Tracking

Authors:
Zhijun Yao;Bin Feng;Junwei Wang;Wenyu Liu
Affiliations:
-;-;-;-
Venue:
AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 03
Year:
2009

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Extracting robust distribution using adaptive Gaussian Mixture Model and online feature selection

Neurocomputing

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Abstract

One of the challenges to creating robust trackers is the construction of robust appearance Model. This paper presents a robust appearance model for object tracking. The robust object distribution is acquired by comparing the two Gaussian Mixture Models of the object and background. The probability image generated by the robust object distribution is used for the CAMSHIFT tracking. Experiments on several video sequences show the effectiveness of the proposed method.