{"title":"基于眼动追踪的驾驶员注意力不集中系统疲劳特征研究","authors":"K. Horak","doi":"10.1109/TSP.2011.6043660","DOIUrl":null,"url":null,"abstract":"This paper deals with segmentation methods and fatigue features determination for a camera-based visual systems monitoring driver vigilance. Generally visual monitoring systems have to analyse a set of computed fatigue features and recognize driver inattention or sleepiness. The paper is focused mostly on the segmentation methods used for reliable eyes tracking because of eyes features are certainly the most significant features for determining of a driver fatigue. Fundamentals segmentation methods as a simple colour segmentation and Hough transform are introduced in the paper. After that a more complex Haar-like features approach and symmetries detection approach are shortly introduced. Finally, several of the leading fatigue features are listed and described. All the presented segmentation methods were tested on both laboratory and real images.","PeriodicalId":341695,"journal":{"name":"2011 34th International Conference on Telecommunications and Signal Processing (TSP)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Fatigue features based on eye tracking for driver inattention system\",\"authors\":\"K. Horak\",\"doi\":\"10.1109/TSP.2011.6043660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with segmentation methods and fatigue features determination for a camera-based visual systems monitoring driver vigilance. Generally visual monitoring systems have to analyse a set of computed fatigue features and recognize driver inattention or sleepiness. The paper is focused mostly on the segmentation methods used for reliable eyes tracking because of eyes features are certainly the most significant features for determining of a driver fatigue. Fundamentals segmentation methods as a simple colour segmentation and Hough transform are introduced in the paper. After that a more complex Haar-like features approach and symmetries detection approach are shortly introduced. Finally, several of the leading fatigue features are listed and described. All the presented segmentation methods were tested on both laboratory and real images.\",\"PeriodicalId\":341695,\"journal\":{\"name\":\"2011 34th International Conference on Telecommunications and Signal Processing (TSP)\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 34th International Conference on Telecommunications and Signal Processing (TSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TSP.2011.6043660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 34th International Conference on Telecommunications and Signal Processing (TSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSP.2011.6043660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fatigue features based on eye tracking for driver inattention system
This paper deals with segmentation methods and fatigue features determination for a camera-based visual systems monitoring driver vigilance. Generally visual monitoring systems have to analyse a set of computed fatigue features and recognize driver inattention or sleepiness. The paper is focused mostly on the segmentation methods used for reliable eyes tracking because of eyes features are certainly the most significant features for determining of a driver fatigue. Fundamentals segmentation methods as a simple colour segmentation and Hough transform are introduced in the paper. After that a more complex Haar-like features approach and symmetries detection approach are shortly introduced. Finally, several of the leading fatigue features are listed and described. All the presented segmentation methods were tested on both laboratory and real images.