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- W3203199522 abstract "Abstract The discriminative correlation filter (DCF)-based tracking methods have achieved remarkable performance in visual tracking. However, the existing DCF paradigm still suffers from dilemmas such as boundary effect, filter degradation, and aberrance. To address these problems, we propose a spatio-temporal joint aberrance suppressed regularization (STAR) correlation filter tracker under a unified framework of response map. Specifically, a dynamic spatio-temporal regularizer is introduced into the DCF to alleviate the boundary effect and filter degradation, simultaneously. Meanwhile, an aberrance suppressed regularizer is exploited to reduce the interference of background clutter. The proposed STAR model is effectively optimized using the alternating direction method of multipliers (ADMM). Finally, comprehensive experiments on TC128, OTB2013, OTB2015 and UAV123 benchmarks demonstrate that the STAR tracker achieves compelling performance compared with the state-of-the-art (SOTA) trackers." @default.
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- W3203199522 date "2021-09-25" @default.
- W3203199522 modified "2023-10-17" @default.
- W3203199522 title "Spatio-temporal joint aberrance suppressed correlation filter for visual tracking" @default.
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- W3203199522 doi "https://doi.org/10.1007/s40747-021-00544-1" @default.
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