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Saliency guided visual tracking via correlation filter with log-Gabor filter
2020
IEEE Access
Correlation filter (CF) based tracking algorithms have tremendously contributed to the field of visual tracking due to the high computational efficiency and competitive performance. Nonetheless, most CF-based trackers are vulnerable to the influence of occlusion and boundary effect, which results in suboptimal performance. In this article, we propose saliency guided visual tracking via correlation filter with log-Gabor filter to robustify its performance under occlusion and boundary effect
doi:10.1109/access.2020.3020304
fatcat:ckdknnqpdne75owcvjfcdx5tue