@inproceedings{dabd24dfd237442d87d734a22d2b3acd,
title = "Driver status recognition by neighborhood covering rules",
abstract = "Driver fatigue recognition based on computer vision is considered as a challenging issue. Though human face carries most information related to human status, the information is redundant and overlapped. In this work, we concentrate on several fatigue indicating areas and three types of features are extracted from them. Then a neighborhood rough set technique is introduced to evaluate quality of candidate features and select the effective subset. A rule learning classifier based on neighborhood covering reduction is employed for the classification task. Compared with classic classifiers, the designed recognition system performs well. The experiments are presented to show the effectiveness of the proposed technique.",
keywords = "fatigue recognition, feature selection, rule learning",
author = "Yong Du and Qinghua Hu and Peijun Ma and Xiaohong Su",
year = "2011",
doi = "10.1007/978-3-642-24425-4\_43",
language = "英语",
isbn = "9783642244247",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "327--336",
booktitle = "Rough Sets and Knowledge Technology - 6th International Conference, RSKT 2011, Proceedings",
note = "6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011 ; Conference date: 09-10-2011 Through 12-10-2011",
}