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Computer vision has received a significant attention in recent year, which isone of the important parts for robots to obtain information about the externalenvironment. Visual trackers can provide the necessary physical andenvironmental parameters for the mobile robot, and their performance is relatedto the actual application of the robot. This study provides a comprehensivesurvey on visual trackers. Following a brief introduction, we first analyzedthe basic framework and difficulties of visual trackers. Then the structure ofgenerative and discriminative methods is introduced, and summarized the featuredescriptors, modeling methods, and learning methods which be used in tracker.Later we reviewed and evaluated the state-of-the-art progress on discriminativetrackers from three directions: correlation filter, deep learning andconvolutional features. Finally, we analyzed the research direction of visualtracker used in mobile robot, as well as outlined the future trends for visualtracker on mobile robot.

A Review of Visual Trackers and Analysis of its Application to Mobile Robot