Learning augmented memory joint aberrance repressed correlation filters for visual tracking

Ji, Yuanfa and He, Jianzhong and Sun, Xiyan and Bai, Yang and Wei, Zhaochuan and Kamarul Hawari, Ghazali (2022) Learning augmented memory joint aberrance repressed correlation filters for visual tracking. Symmetry, 14 (1502). pp. 1-19. ISSN 2073-8994. (Published)

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With its outstanding performance and tracking speed, discriminative correlation filters (DCF) have gained much attention in visual object tracking, where time-consuming correlation operations can be efficiently computed utilizing the discrete Fourier transform (DFT) with symmetric properties. Nevertheless, the inherent issues of boundary effects and filter degradation, as well as occlusion and background clutter, degrade the tracking performance. In this work, we proposed an augmented memory joint aberrance repressed correlation filter (AMRCF) for visual tracking. Based on the background-aware correlation filter (BACF), we introduced adaptive spatial regularity to mitigate the boundary effect. Several historical views and the current view are exploited to train the model together as a way to reinforce the memory. Furthermore, aberrance repression regularization was introduced to suppress response anomalies due to occlusion and deformation, while adopting the dynamic updating strategy to reduce the impact of anomalies on the appearance model. Finally, extensive experimental results over four well-known tracking benchmarks indicate that the proposed AMRCF tracker achieved comparable tracking performance to most state-of-the-art (SOTA) trackers.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Aberrance repression; Augmented memory; Discriminative correlation filter; Visual object tracking
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical and Electronic Engineering Technology
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 07 Feb 2024 07:19
Last Modified: 07 Feb 2024 07:19
URI: http://umpir.ump.edu.my/id/eprint/40157
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