Research on a multi-scale traffic scene object detection algorithm based on Light-YOLOX

Yao Wang; Xing Liu

doi:10.1117/12.3025882

6 May 2024 Research on a multi-scale traffic scene object detection algorithm based on Light-YOLOX

Yao Wang, Xing Liu

Proceedings Volume 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023); 131610N (2024) https://doi.org/10.1117/12.3025882
Event: Fourth International Conference on Telecommunications, Optics and Computer Science (TOCS 2023), 2023, Xi’an, China

Abstract

A multi-scale traffic scene object detection algorithm based on Light-YOLOX has been proposed with the aim of achieving a substantial enhancement in accuracy while maintaining a lightweight design. To accomplish this, the algorithm has undergone further refinement by introducing a pyramidal attention segmentation module in the backbone network and pooling structure. This enhancement has significantly improved the algorithm’s capacity to extract contextual information at various scales, leading to more precise and comprehensive object detection in traffic scenes. Moreover, the development of the Py-FPN feature fusion structure, achieved through the integration of multi-scale pyramidal convolution, has enabled the complete fusion of output feature layers from the backbone network. This integration has further heightened the algorithm’s detection effectiveness, ensuring a more robust and accurate detection of objects within traffic scenes. Through experimental evaluations on both the KITTI dataset and Cityscapes dataset, it has been demonstrated that the proposed multi-scale traffic scene object detection method delivers a considerable improvement in accuracy and comprehensive performance, despite having a minimal number of parameters and operations. These findings underscore the algorithm’ s potential applicability and effectiveness in the practical field of traffic scene object detection, illustrating its suitability for real-world deployment and utilization.

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

Citation Download Citation

Yao Wang and Xing Liu "Research on a multi-scale traffic scene object detection algorithm based on Light-YOLOX", Proc. SPIE 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023), 131610N (6 May 2024); https://doi.org/10.1117/12.3025882

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KEYWORDS

Convolution

Detection and tracking algorithms

Object detection

Education and training

Feature fusion

Target detection

Data modeling

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