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Visual Tracking via a Novel Adaptive Anti-occlusion Mean Shift Embedded Particle Filter

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Abstract

Visual tracking is a significant research field in computer vision. Despite the development of numerous algorithms, the challenge of achieving effective visual tracking in dynamic environments persists. Among various methods, the particle filter (PF) excels in visual tracking due to its adaptability in nonlinear and non-Gaussian environments. In this article, a novel adaptive anti-occlusion mean shift embedded particle filter (AAO-MSPF) is presented as a distinctive approach to address complex tracking scenarios. The integration of the mean shift algorithm can significantly elevate particle prediction accuracy within the framework. The incorporation of the modified particle swarm optimization algorithm optimizes particle distribution and significantly improves the tracking performance. Furthermore, the proposed anti-occlusion module utilizes block-based detection to identify occlusion, enabling adjustments to the motion model. This technique contributes to improved tracking performance, distinguishing our method from others. After a comprehensive comparative analysis, the experimental results indicate that the proposed method AAO-MSPF demonstrates robustness and stability under challenging dynamic conditions and surpasses other trackers in tracking performance.

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Data Availibility

The OTB-100 dataset used in this research is publicly available. It can be downloaded at https://github.com/yuyma/OTB100_dataset_download/releases.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 62003083, in part by the Fundamental Research Funds for the Central Universities, and in part by the DHU Distinguished Young Professor Program under Grant 23D210401.

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  1. College of Information Science and Technology, Donghua University, Shanghai, 201620, China

    Suyi Xu & Hongwei Chen

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  1. Suyi Xu
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  2. Hongwei Chen
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Correspondence to Hongwei Chen.

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Xu, S., Chen, H. Visual Tracking via a Novel Adaptive Anti-occlusion Mean Shift Embedded Particle Filter. Circuits Syst Signal Process (2024). https://doi.org/10.1007/s00034-024-02882-0

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