Mr. Liang Hu Profile

Liang Hu

at Central South Univ

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Proceedings Article | 27 March 2022 Paper

LSS target tracking algorithm based on optical flow detection and polynomial fitting relocation

Degui Yang, Liang Hu, Junchao Zhang, Dangjun Zhao, Xing Wang, Zhenghong Peng

Proceedings Volume 12169, 12169C9 (2022) https://doi.org/10.1117/12.2627201

KEYWORDS: Detection and tracking algorithms, Target detection, Optical flow, Optical tracking, Image processing, Filtering (signal processing), Distortion, Image filtering

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It’s difficult to detect LSS(Low-Small-Slow) target because of its overturning, distortion during movement. Aiming at this problem, this paper proposes a LSS target tracking algorithm based on optical flow detection and polynomial fitting relocation. Firstly, target is detected by optical flow method, and then the SVM classifier trained with hog feature and color histogram feature is used to eliminate the false target. Then use TBD strategy to process the target information in the first three frames to confirm the initial location of the target. In follow-up tracking process, the obtained target information is compared with polynomial fitting results to determine whether to trigger the relocation mechanism. In relocation mechanism, the hot spot region will be generated according to the polynomial fitting results, and the salient features of the hot spot region will be extracted to determine the target location. Through the performance on the public data set LaSOT and the image sequence collected by the author, the algorithm in this paper is insensitive to the maneuver and distortion of LSS targets, and the tracking effect is stable. Under certain constraints, the tracking accuracy of the algorithm can reach more than 96%, which has strong application value.

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