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Improving the anti-occlusion ability of correlation filter-based trackers via segmentation

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Abstract

In recent years, correlation filter (CF)-based trackers have undergone rapid development and achieved state-of-the-art performance. However, CF-based trackers lack the ability to perceive the local variation of the target, such as occlusion, because they rely on the features from a bounding box to distinguish the target. In contrast, segmentation-based trackers, which distinguish the target based on pixel- or superpixel-level information, can sufficiently perceive local variation. However, their robustness is inferior to that of CF methods due to the lack of high-level semantic information. In this research, the advantages of both methods were combined to improve the anti-occlusion ability of CF trackers. The image segmentation-based occlusion estimation agency (ISBOEA) method is proposed to perceive occlusions, after which the occlusion information is used to guide the training and searching of CF trackers. In experiments conducted in this study, two CF-based trackers, namely the background-aware CF (BACF) and the efficient convolution operators: hand-crafted feature version (ECO_HC), were employed as baselines for tracking. Moreover, the minimum barrier distance (MBD) transform method was employed to conduct image segmentation. Extensive experiments were performed on standard benchmark datasets, namely OTB50, OTB100, GOT-10k and VIVID. The results demonstrate that the proposed ISBOEA method can remarkably improve the anti-occlusion ability of CF-based trackers.

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Authors and Affiliations

  1. Institute of Remote Sensing and Geographic Information System,Key Laboratory of Spatial Information Integration and 3S Engineering Application, Peking University, 100871, Beijing, China

    Kaiwen Jiang, Lei Yan, Zihan Zhang & Hongying Zhao

  2. Guangxi Key Lab of UAV Remote Sensing, Guilin University of Aerospace Technology, 541004, Guilin, China

    Lei Yan

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  1. Kaiwen Jiang
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  2. Lei Yan
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  3. Zihan Zhang
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  4. Hongying Zhao
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Correspondence to Hongying Zhao.

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Jiang, K., Yan, L., Zhang, Z. et al. Improving the anti-occlusion ability of correlation filter-based trackers via segmentation. Appl Intell 53, 2815–2824 (2023). https://doi.org/10.1007/s10489-021-03058-y

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