基于时空特征序列的驾驶员疲劳识别算法

Chen Zhang, Xiaobo Lu, Zhiliang Huang
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引用次数: 5

摘要

研究表明,疲劳驾驶是道路交通事故发生的重要原因之一,因此研究驾驶员疲劳识别算法对提高道路交通安全具有重要意义。近年来,随着深度学习的发展,模式识别领域取得了很大的发展。本文设计了一种基于时空特征序列的实时疲劳状态识别算法,主要应用于疲劳驾驶场景识别。该算法分为三个任务网络:人脸检测网络、人脸地标检测和头姿估计网络、疲劳识别网络。实验表明,该算法具有体积小、速度快、精度高等优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Driver Fatigue Recognition Algorithm Based on Spatio-Temporal Feature Sequence
Researches show that fatigue driving is one of the important causes of road traffic accidents, so it is of great significance to study the driver fatigue recognition algorithm to improve road traffic safety. In recent years, with the development of deep learning, the field of pattern recognition has made great development. This paper designs a real-time fatigue state recognition algorithm based on spatio-temporal feature sequence, which can be mainly applied to the scene of fatigue driving recognition. The algorithm is divided into three task networks: face detection network, facial landmark detection and head pose estimation network, fatigue recognition network. Experiments show that the algorithm has the advantages of small volume, high speed and high accuracy.
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