Paper
8 June 2023 Development of a heavy truck reversing safety system based on pedestrian detection and tracking using binocular vision stitching
Jiaxi Yu, Xiaoping Wu, Dongyang Li, Linhai Lu
Author Affiliations +
Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 1270702 (2023) https://doi.org/10.1117/12.2680921
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China
Abstract
The large blind region behind the huge body of a truck is the primary reason for reversing collisions. However, there are few truck reversing auxiliary approaches to avoid reversing accidents. In this paper, we present a novel heavy truck reversing safety approach based on pedestrian detection and tracking using binocular vision stitching. The proposed system contains three primary steps: binocular vision stitching, pedestrian detection and tracking, and heavy truck reversing speed control method. First of all, a binocular camera system based on vision stitching is used to perceive the reversing environment of the heavy truck. Secondly, the framework of YOLOv3 and discriminative correlation filter based tracking method is used to detect and track the pedestrian in real time. The pedestrian feature is extracted with improved MobileNetV2. Finally, a heavy truck reversing speed control method which can automatically control the reversing speed to avoid collisions improves the safety of truck reversing. This system has been tested on a van truck. Experiments demonstrate the viability of the proposed heavy truck reversing safety system.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiaxi Yu, Xiaoping Wu, Dongyang Li, and Linhai Lu "Development of a heavy truck reversing safety system based on pedestrian detection and tracking using binocular vision stitching", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 1270702 (8 June 2023); https://doi.org/10.1117/12.2680921
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KEYWORDS
Safety

Detection and tracking algorithms

Binocular vision

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