A robust mean-shift tracking through occlusion and scale based on object trajectory for surveillance camera

Hocine Labidi; Sen-Lin Luo; Mohamed Bachir Boubekeur

doi:10.1117/12.2179343

4 March 2015 A robust mean-shift tracking through occlusion and scale based on object trajectory for surveillance camera

Hocine Labidi, Sen-Lin Luo, Mohamed Bachir Boubekeur

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Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94432C (2015) https://doi.org/10.1117/12.2179343
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China

Abstract

Object tracking is an important part in surveillance systems, One of the algorithms used for this task is the meanshift algorithm due to the robustness, computational efficiency and implementation ease. However the traditional meanshift cannot effectively track the moving object when the scale changes, because of the fixed size of the tracking window, and can lose the target while an occlusion, In this study a method based on the trajectory direction of the moving object is presented to deal with the problem of scale change. Furthermore a histogram similarity metric is used to detect when target occlusion occurs, and a method based on multi kernel is proposed, to estimate which part is not in occlusion and this part will be used to extrapolate the motion of the object and gives an estimation of its position, Experimental results show that the improved methods have a good adaptability to the scale and occlusion of the target.

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Hocine Labidi, Sen-Lin Luo, and Mohamed Bachir Boubekeur "A robust mean-shift tracking through occlusion and scale based on object trajectory for surveillance camera ", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432C (4 March 2015); https://doi.org/10.1117/12.2179343

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KEYWORDS

Detection and tracking algorithms

Target detection

Cameras

Algorithm development

Motion estimation

Surveillance

Surveillance systems

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