Object tracking based on extended SURF and particle filter

Authors:
Min Niu;Xiaobo Mao;Jing Liang;Ben Niu
Affiliations:
School of Electrical Engineering, Zhengzhou University, Zhengzhou, China;School of Electrical Engineering, Zhengzhou University, Zhengzhou, China;School of Electrical Engineering, Zhengzhou University, Zhengzhou, China;College of Management, Shenzhen University, Shenzhen, China
Venue:
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
Year:
2013

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Abstract

Under complex environment, it is difficult to track target successfully by single feature. To solve this problem, the paper propose a novel object tracking approach which fuses color and SURF(Speeded Up Robust Features) in the frame of particle filter. SURF remain invariant for illumination, scale and affine. Add color to make up for the shortcoming(SURF is based on image gray scale information.). It not only maintains the characteristics of SURF, but also makes use of the image color information. The experimental results prove that the proposed method is real-time and robust in different scenes.