Video-based detection and classification of driving postures by feature distance extraction and BP neutral network

Hui Tang; Jie He; Youfeng Zheng; Jun Zhang; Lin Wei

doi:10.1117/12.2540471

31 July 2019 Video-based detection and classification of driving postures by feature distance extraction and BP neutral network

Hui Tang, Jie He, Youfeng Zheng, Jun Zhang, Lin Wei

Author Affiliations +

Proceedings Volume 11198, Fourth International Workshop on Pattern Recognition; 111980G (2019) https://doi.org/10.1117/12.2540471
Event: Fourth International Workshop on Pattern Recognition, 2019, Nanjing, China

Abstract

At present, academic research mainly focuses on detecting driver fatigue and distraction through the driver's eyes and head. But there are few studies on detecting driving behavior through the head, hands and even the body, most of which use the skin color detection method to extract a single full-image pixel as a feature and the dimension is too large, problems such as instantaneous region overlap and partial occlusion occur inevitably in the detection process, thereby affecting the detection accuracy. In this paper, we propose a driving posture detection method based on video and skin color region distance. The image features are represented by extracting the skin color region centroid coordinates of the sampled images from videos and converting them into feature distances. Then the BP neural network is used to implement the identification and classification of driving behavior, which can effectively improve the detection rate of the driving behavior, and finally realize the real-time warning of the driving process.

Citation Download Citation

Hui Tang, Jie He, Youfeng Zheng, Jun Zhang, and Lin Wei "Video-based detection and classification of driving postures by feature distance extraction and BP neutral network", Proc. SPIE 11198, Fourth International Workshop on Pattern Recognition, 111980G (31 July 2019); https://doi.org/10.1117/12.2540471

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