旋转自适应的多特征融合多模板学习视觉跟踪算法

doi:10.16451/j.cnki.issn1003-6059.202109002

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Abstract Visual target tracking remains a hard problem due to unpredictable target rotation and external interference. To address this issue, a target tracking algorithm based on rotation adaptation, multi-feature fusion and multi-template learning(RA-MFML) is proposed. Firstly, a multi-template learning model with complementary characteristics is constructed. The global filter template is used for tracking the target. When the global filter template is determined to be contaminated by the decidable filter template, it is corrected by the modified filter template. Then, the color histogram is regarded as visual supplementary information and fused with feature map of VGGNet-19 adaptively. The discriminating ability of the global filter template for object appearance is thus improved. Finally, a rotation adaptation strategy is proposed. The improved tracking confidence is utilized for the estimation of the optimal rotation angle of the tracking box to alleviate performance degradation of the global filter template caused by target rotation. The experiment on OTB-2013 and OTB-2015 datasets demonstrate that RA-MFML is superior in success rate and precision.

Key words： Target Tracking Global Filter Template Rotation Adaptation Tracking Confidence

Received: 20 April 2021

ZTFLH:

TP 391.41

Fund:National Natural Science Foundation of China(No.6187307,61401129), Key Research and Development Program of Zhejiang Province(No.2018C01069)

Corresponding Authors: HE Zhiwei, Ph.D., professor. His research interests include machine learning and object tracking.

About author:: DU Chenjie, Ph.D. candidate. His research interests include object detection and tracking.
YANG Yuxiang, Ph.D., associate profe-ssor. His research interests include deep learning and object tracking.
WU Han, master student. His research interests include object detection and tracking.
GAO Mingyu, Ph.D., professor. His research interests include video/image proce-ssing.

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Cite this article:

DU Chenjie,YANG Yuxiang,WU Han等. Visual Tracking Algorithm Based on Rotation Adaptation, Multi-feature Fusion and Multi-template Learning[J]. , 2021, 34(9): 787-797.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202109002 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2021/V34/I9/787

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