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《Control and Decision》 2016-02
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Person tracking for robot using patches-based-multi-cues representation

WANG Li-jia;JIA Song-min;LI Xiu-zhi;LU Ying-bin;College of Electronic Information & Control Engineering,Beijing University of Technology;Beijing Key Laboratory of Computational Intelligence and Intelligent System;Department of Information Engineering and Automation,Hebei College of Industry and Technology;  
To deal with the problem of occlusion and appearance changes in person tracking with a mobile robot, an algorithm based on patches-based-multi-cues representation is proposed. The algorithm segments the candidate sample and extracts the depth information, color histograms, texture histograms from each image slice for constructing the detector.A motion extended Kalman filter(MEKF) is obtained by considering the motion of the robot and target. As tracking evolves, the target's size is adaptively adjusted according to the depth histogram. Furthermore, occlusion is identified by simultaneously detecting the depth features and appearance model. Experiments results show that the proposed approach has better robustness for dealing with the problem of scale changes, illumination variations, and occlusion.
【Fund】: 国家自然科学基金项目(61175087;61105033);; 河北省科技支撑计划项目(14275601D)
【CateGory Index】: TP391.41
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