@inproceedings{178ceecf89c44fb5b81e65e8b7a3364c,
title = "Driver drowsiness detection through HMM based dynamic modeling",
abstract = "Drowsiness is one of the main causes of severe traffic accidents occurring in our daily life. In order to reduce the number of drowsiness-induced accidents, various researches have been conducted with the aim of finding practical and non-invasive drowsiness detection systems by using behavioral measuring techniques. Many of the previous works on behavioral measuring techniques have mainly focused on the analysis of eye closure and blinking of the driver. It is recently that more attention started to shift to inclusion of other facial expressions and only few, among those researches, have been done on the analysis of temporal dynamics of facial expressions for drowsiness detection. In this paper we propose a new method of analyzing the facial expression of the driver through Hidden Markov Model (HMM) based dynamic modeling to detect drowsiness. We have implemented the algorithm using a simulated driving setup. Experimental results verified the effectiveness of the proposed method.",
keywords = "Drowsiness detection, HMM, SVM, facial expression",
author = "Eyosiyas Tadesse and Weihua Sheng and Meiqin Liu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Robotics and Automation, ICRA 2014 ; Conference date: 31-05-2014 Through 07-06-2014",
year = "2014",
month = sep,
day = "22",
doi = "10.1109/ICRA.2014.6907440",
language = "英语",
series = "Proceedings - IEEE International Conference on Robotics and Automation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4003--4008",
booktitle = "Proceedings - IEEE International Conference on Robotics and Automation",
}
