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1 August 2023 Pedestrian multi-object tracking based on YOLOv7 and BoT-SORT
Tingting Li, Zhanbo Li, Yuhong Mu, Jie Su
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Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127541I (2023) https://doi.org/10.1117/12.2684256
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China
Abstract
As a crucial component in the realm of computer vision, multi-object tracking has garnered widespread application in areas such as autonomous driving, smart transportation, and surveillance technology.Based on YOLOv7 and BoT-SORT algorithms, this paper followed TBD (track by detection) framework. First, YOLOv7 served as the detector tasked with identifying the target and specifying its location within the frame. Then, the BoT-SORT algorithm was used to track the target based on the target detection results. The results are then tested on the MOT20 dataset. The experimental data show that on MOT20 data set, the accuracy of multi-object tracking reaches 69.36%, and the accuracy of multi-object tracking reaches 79.11%, which effectively solves the problems of target occlusion and frequent identity switching. The experiment proves that it still has good tracking effect under dim lighting and crowded complex scenes. It can achieve better tracking for the non-rigid target of pedestrians, and has higher accuracy than YOLOv7-DeepSORT and YOLOv7-ByteTrack.
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Tingting Li, Zhanbo Li, Yuhong Mu, and Jie Su "Pedestrian multi-object tracking based on YOLOv7 and BoT-SORT", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127541I (1 August 2023); https://doi.org/10.1117/12.2684256
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KEYWORDS
Object detection
Detection and tracking algorithms
Target detection
Video
Video surveillance
Cameras
Switches
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