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Date of Publication:2020-01-01

Journal:Computer Engineering and Application

Volume:56

Issue:14

Page Number:161-168

ISSN No.:1002-8331

Key Words:"target tracking; depth information; Kernelized Correlation Filters(KCF); mobile robot"

CN No.:11-2127/TP

Abstract:In complex scenes and drastic changes in target appearance, the tracking model of the Kernelized Correlation Filter(KCF) method is susceptible to interference, which results in the problem that the tracking window is not adaptive and the target is lost. To this end, a mobile robot tracking system based on depth information is proposed. The target scale frame is estimated by Cross-Searching Edge(CSE) method, and the tracking failure is checked by fluctuations in axial relative kinetic energy method. The target loss is recovered by scale pool and search strategy. Experimental results show that the proposed method combining KCF and scene depth information can effectively realize target tracking window self-adaptation and target recovery after losing, which has a stable application effect on mobile robots.

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