Research on key technologies for rapid collection of traffic signs based on binocular vision

Zhi Lou; Weidong Song; Shangyu Sun; Jiakai Fan

doi:10.1117/12.3031065

19 July 2024 Research on key technologies for rapid collection of traffic signs based on binocular vision

Zhi Lou, Weidong Song, Shangyu Sun, Jiakai Fan

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 1318129 (2024) https://doi.org/10.1117/12.3031065
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

Traffic signs, as critical assets on highways, play a crucial role in road safety, traffic flow optimization, and intelligent transportation systems. In urban road environments, the influence of factors such as urban greenery and buildings leads to the occlusion of traffic signs and the complexity of the background environment, making the detection process more intricate and challenging. Against the backdrop of the diversity and variability of urban environments, this paper proposes a method for the rapid collection of traffic signs that integrates binocular vision and computer vision. Firstly, data collection and preprocessing are accomplished using a binocular camera mounted on a mobile measurement collection vehicle. Subsequently, our proposed fast detection and localization method are applied to detect and track objects in the left image, followed by matching detections in the right image. The detection results from both images are then matched, and the disparity is calculated. Finally, combining the results with the calibration information from the binocular camera and feedback from a programmable controller, the position information of traffic signs is obtained. Experimental validation demonstrates that our proposed fast detection and localization method achieves a detection accuracy and recall rate of 95% and 97%, respectively, showing robustness against occlusion and complex backgrounds.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhi Lou, Weidong Song, Shangyu Sun, and Jiakai Fan "Research on key technologies for rapid collection of traffic signs based on binocular vision", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 1318129 (19 July 2024); https://doi.org/10.1117/12.3031065

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KEYWORDS

Object detection

Target detection

Roads

Cameras

Calibration

Binocular vision

Convolution

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