Research on pedestrian distance detection algorithm Based on perspective transformation

Yan Qi; Zipeng Yu; Dawei Yang; Lei Chu

doi:10.1117/12.2675239

25 May 2023 Research on pedestrian distance detection algorithm Based on perspective transformation

Yan Qi, Zipeng Yu, Dawei Yang, Lei Chu

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126361W (2023) https://doi.org/10.1117/12.2675239
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

This paper introduces perspective transformation method to improve the error caused by perspective problem in pedestrian distance detection in complex scenes. In this paper, YOLOv5 target detection algorithm is adopted, and perspective transformation algorithm is introduced in the input. It is hoped that by calibrating the video input, the camera view can be transformed into a bird's eye view after perspective transformation, so as to ensure accurate distance between detected targets. It can be seen from the experimental results that the improved YOLOv5 has a good effect on the distance accuracy of pedestrian distance detection, making the accuracy rate reach 89.63%.

Citation Download Citation

Yan Qi, Zipeng Yu, Dawei Yang, and Lei Chu "Research on pedestrian distance detection algorithm Based on perspective transformation", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126361W (25 May 2023); https://doi.org/10.1117/12.2675239

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