• Laser & Optoelectronics Progress
  • Vol. 60, Issue 10, 1010021 (2023)
Xiao Yun*, Kaili Song, Xiaoguang Zhang, and Xinchao Yuan
Author Affiliations
  • School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221008, Jiangsu, China
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    DOI: 10.3788/LOP220812 Cite this Article Set citation alerts
    Xiao Yun, Kaili Song, Xiaoguang Zhang, Xinchao Yuan. Occluded Video-Based Person Re-Identification Based on Spatial-Temporal Trajectory Fusion[J]. Laser & Optoelectronics Progress, 2023, 60(10): 1010021 Copy Citation Text show less

    Abstract

    Aiming at the problem of wide-range occlusion of target pedestrians in video pedestrian re-identification, a pedestrian re-identification algorithm based on spatio-temporal trajectory fusion is proposed by combining pedestrian trajectory prediction with pedestrian re-identification, which is time-related and not affected by occlusion. First, from the time and space domains, accurate pedestrian trajectory coordinate prediction in line with social attributes is realized. Second, the spatiotemporal trajectory fusion feature is constructed to effectively combine the apparent visual features in the video sequence with the coordinate data in the pedestrian trajectory, which effectively alleviates the impact of centralized occlusion on the re-identification performance. Finally, a trajectory fusion dataset MARS_traj suitable for the proposed algorithm is constructed, and experiments show that the proposed algorithm can effectively improve the performance of the occlusion video re-identification.
    Xiao Yun, Kaili Song, Xiaoguang Zhang, Xinchao Yuan. Occluded Video-Based Person Re-Identification Based on Spatial-Temporal Trajectory Fusion[J]. Laser & Optoelectronics Progress, 2023, 60(10): 1010021
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