Prof. Dan Tian Profile

Prof. Dan Tian

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Proceedings Article | 4 March 2024 Paper

Robust long-term target tracking algorithm based on objectness-guided tracking

Dan Tian, Yuxin Wang, Ying Hao

Proceedings Volume 12981, 1298164 (2024) https://doi.org/10.1117/12.3014914

KEYWORDS: Target detection, Detection and tracking algorithms, Image enhancement, Chemical species, Video surveillance, Video, Education and training, Deep learning, Video processing, RGB color model

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Compared with short-term target tracking, long-term target tracking requires processing of long video sequences and scenes in which the target disappears and reappears. These scenarios are closer to reality, so the research of long-term target tracking algorithms is more practical. In this paper, the long-term target tracking algorithm is divided into two parts, local tracking and global detection. The local tracking module adopts Siam RPN framework, which can not only give the optimal candidate when the target exists, but also accurately determine the target does not exist when the target disappears and enter the global detection module. For the global detection, we propose a new global detection module, which directly predicts the size and position of the target on the whole image based on the target guidance, solves the problem of the original block technology, and greatly improves the tracking speed and accuracy. A large number of experimental results on the VOT-2018LT benchmark show that the proposed method achieves the best performance.

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