Affiliation:
1. School of Computer and Software Engineering, Xihua University, Chengdu, Sichuan 610039, P. R. China
2. College of Big Data Statistics, Guizhou University of Finance and Economics, Guiyang 550025, P. R. China
Abstract
It is an obvious fact that drivers’ drowsiness is more likely to cause traffic accidents. Recently, driver drowsiness detection has drawn considerable attention. In this paper, a novel drowsiness detection scheme is proposed, which can recognize drivers’ drowsiness actions through their facial expressions. First, a drowsiness action recognition model based on 3D-CNN is proposed, which can effectively distinguish drivers’ drowsiness actions and nondrowsiness actions. Second, a fusion algorithm of the two input streams is proposed, which can fuse gray image sequence and optical image sequence containing target motion information. Finally, the proposed model is evaluated on National Tsinghua University Driver Drowsiness Detection (NTHU-DDD) dataset. The experimental results show that the algorithm performs better than other algorithms, and its accuracy reaches 86.64%.
Funder
Department of Science and Technology of Sichuan Province
Funds Project of Chengdu Science and Technology Bureau
the National Natural Science Foundation of China
the Fund of Sichuan Educational Committee
the Foundation of Cyberspace Security Key Laboratory of Sichuan Higher Education Institutions and Sichuan Youth Science and technology innovation research team
Publisher
World Scientific Pub Co Pte Ltd
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Cited by
5 articles.
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