A Particle Filter Infrared Target Tracking Method Based on Multi-feature Adaptive Fusion

CHONG Yanwen; WANG Zewen; CHEN Rong; WANG Yingying

doi:10.13203/j.whugis20140185

Volume 41 Issue 5

May 2016

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Geomatics and Information Science of Wuhan University > 2016 > 41(5): 598-604. > DOI: 10.13203/j.whugis20140185

CHONG Yanwen, WANG Zewen, CHEN Rong, WANG Yingying. A Particle Filter Infrared Target Tracking Method Based on Multi-feature Adaptive Fusion[J]. Geomatics and Information Science of Wuhan University, 2016, 41(5): 598-604. DOI: 10.13203/j.whugis20140185

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A Particle Filter Infrared Target Tracking Method Based on Multi-feature Adaptive Fusion

1.
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
2.
Research Institute of Hangzhou Hikvision Digital Technology Co., Ltd, Hangzhou 310051, China

Funds: The National Natural Science Foundation of China, No. 41271398; the Fundamental Research Funds for the Central Universities, Nos. 2042014kf0242, 2042014kf0263.

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Received Date: May 07, 2014
Published Date: May 04, 2016

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Abstract

Abstract

In infrared target tracking it is difficult to predict the existence of background interference as there is a contradiction between the real-time and effectiveness of the algorithms. Hence this paper presents a particle filter tracking algorithm based on adaptive fusion of color features and edge features. Using the natural frame work of a particle filter, with infrared conditions it selects color features and edge features that best represent the target information to construct the multi-feature model of the target. According to the different feature separability of target and background, the weight of each feature component of a multi-feature is adaptively adjusted. This dynamic space model improves the particle filter tracking algorithm to predict the motion state of the particles to overcome the effects of environment mutations on tracking stability. Experimental results show that the proposed algorithm can overcome interference from all kinds of background clutter and noise ensuring tracking robustness and accuracy.
- infrared,
- multi-feature fusion,
- particle filter,
- dynamic spatial model,
- target tracking

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A Particle Filter Infrared Target Tracking Method Based on Multi-feature Adaptive Fusion

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