Fuzzy Color Histogram Based Kernel Tracking under Varying Illumination

Authors:
Yongzhong Wang;Quan Pan;Chunhui Zhao;Yongmei Cheng
Affiliations:
College of Automation, Northwestern Polytechnical University, Xi'an, P. R. China;College of Automation, Northwestern Polytechnical University, Xi'an, P. R. China;College of Automation, Northwestern Polytechnical University, Xi'an, P. R. China;College of Automation, Northwestern Polytechnical University, Xi'an, P. R. China
Venue:
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04
Year:
2007

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Kernel-based object tracking using a simple fuzzy color histogram

IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I

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Abstract

A conventional color histogram is sensitive to noisy interference such as lighting changes and quantization errors. Therefore the tracker based on conventional color histogram is unreliable or even failed under varying illumination. In this paper we propose a dynamically corrected fuzzy color histogram based kernel tracking algorithm, which utilizes the local background information around tracking target to dynamically correct its fuzzy color histogram model and eliminates the sensitive of conventional color histogram to illumination change and noise. The algorithm is tested on several image sequences and shown that it can smooth the similarity surface and achieve robust and reliable frame-rate tracking results under varying illumination conditions.