Eye Statement Recognition for Driver Fatigue Detection Based on Gabor Wavelet and HMM

摘要：

Eye statement is one of the most important factors reflecting driver fatigue. A novel eye statement recognition method for driver fatigue detection based on Gabor transformation and Hidden Markov Model is proposed in this paper, in which, the eye detection algorithm is borrowed from Zafer Savas TrackEye software, and Gabor features, i.e. the eye state features, of the eye are extracted by using Gabor wavelet. After that, by using these features, the classifier is trained by HMM (Hidden Markov Model) to distinguish the eye states including fatigue and alert, then the consecutive five frames are considered to judge whether there exists driver fatigue or not. Simulation results show that the new method has good accuracy and effectiveness.

关键词： Fatigue Monitoring Gabor translation Hidden Markov Model

作者: Haiyan Yang Xinhua Jiang Lei Wang Yonghui Zhang

作者单位: Information Science and Technology School,Central South University,Changsha,Hunan,China Institute of Information Science and Technology School,Central South University,Changsha,Hunan,China Institute of Control and Information Technology.Fujian University of Technology, Fuzhou,Fujian,China Information Science and Technology School,Central South University, Changsha,Hunan,China

会议类型: 国际会议

会议名称: 4th International Conference on Measuring Technology and Mechatronics Automation(第四届检测技术与机电自动化国际会议 ICMTMA 2012)

会议地点: 三亚

会议语种:英文

页码: 123-129

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）