在线判别式超像素跟踪算法

doi:10.3969/j.issn.1001-2400.2018.03.003

Abstract

Abstract:

In order to solve the problems of slow modeling speed and target occlusion easy drift of the traditional superpixel tracking method, a new target tracking method is proposed. The new proposed method uses superpixel segmentation to obtain a large number of target foreground and backgroundsuperpixel training data. By training the extreme learning machine and combining with the k-d tree clustering we can obtain a discriminant model of the target and background discriminant model quickly.In the tracking process, the constructed modeland the particle filter are used to estimate the target center position. Finally, the target scale information is estimated by correlation filtering to achieve the robustness tracking of the target. Experimental results show that the proposed algorithm has a reliable tracking accuracy and a fast tracking speed.

Key words: target tracking, superpixel, extreme learning machine, correlation methods

LIU Yuqing;XIAO Song;LI Lei. Online discriminant based superpixel tracking method[J].Journal of Xidian University, 2018, 45(3): 13-17+168.

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Online discriminant based superpixel tracking method

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