An improved anti-occlusion FDSST algorithm with SSDA

Zhujun Liang; Xingping Zhang; Yanhua Shao

doi:10.1117/12.2589439

27 January 2021 An improved anti-occlusion FDSST algorithm with SSDA

Zhujun Liang, Xingping Zhang, Yanhua Shao

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 117200K (2021) https://doi.org/10.1117/12.2589439
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

Aiming at the occlusion problem in the target tracking algorithm FDSST (Fast Discriminative Scale Space Tracking), this paper designs an improved SSDA (Sequential Similarity Detection Algorithms)-based FDSST anti-occlusion algorithm. The algorithm mainly improves the model update strategy of FDSST, the main processes are as follows: Firstly, judge whether the target has occlusion according to the oscillation degree of the correlation filter response graph; then, when there is occlusion, the SSDA algorithm is applied to re-detect the target according to the search strategy, to restore the occluded target and re-track the target. Our method was transplanted to onboard Jetson TX2, and the actual test was carried out on the public dataset OTB50 and the aerial video dataset respectively. The experimental results show that the proposed algorithm retains the advantages of FDSST and improves its anti-occlusion ability effectively.

Citation Download Citation

Zhujun Liang, Xingping Zhang, and Yanhua Shao "An improved anti-occlusion FDSST algorithm with SSDA", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 117200K (27 January 2021); https://doi.org/10.1117/12.2589439

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