Sparse representation tracking method based on locality sensitive histogram

GE Kairong, CHANG Faliang, DONG Wenhui

1. School of Control Science and Engineering, Shandong University, Jinan 250061, China
• Received:2014-03-27 Revised:2014-09-24 Published:2014-03-27

Abstract: In order to solve the problems of illumination and pose change during target tracking, a sparse representation tracking method based on local sensitive histogram was proposed. Local sensitive histogram features of multiple candidate targets were extracted, and sparse representation coefficient of each candidate target was calculated based on template dictionary by using modified L1 norm model. Then, the weight of each candidate target was calculated. The candidate target which had the largest weight was selected as tracking result. Experimental results demonstrated that the method can track the target accurately and effectively and has advantage in illumination and pose change.

CLC Number:

• TP391.4
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