{"title":"基于小波变换的驱动疲劳检测研究","authors":"Mingwang Mao, Liping Du","doi":"10.1109/ICVES.2007.4456391","DOIUrl":null,"url":null,"abstract":"Driver fatigue is an important factor causing serious traffic accidents and often results in many people deaths or injuries. Therefore, many countries have made great effort on how to detect driver fatigue. This paper presents a new approach to detect driver fatigue based on discrete wavelet transform which has been used to extract the key features for constructing the classifier to identify driver fatigue. . The analyzed data are obtained from experiments using driving simulator. The result proves the algorithm is valid.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Research on drive fatigue detection using wavelet transform\",\"authors\":\"Mingwang Mao, Liping Du\",\"doi\":\"10.1109/ICVES.2007.4456391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Driver fatigue is an important factor causing serious traffic accidents and often results in many people deaths or injuries. Therefore, many countries have made great effort on how to detect driver fatigue. This paper presents a new approach to detect driver fatigue based on discrete wavelet transform which has been used to extract the key features for constructing the classifier to identify driver fatigue. . The analyzed data are obtained from experiments using driving simulator. The result proves the algorithm is valid.\",\"PeriodicalId\":202772,\"journal\":{\"name\":\"2007 IEEE International Conference on Vehicular Electronics and Safety\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Conference on Vehicular Electronics and Safety\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVES.2007.4456391\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Vehicular Electronics and Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVES.2007.4456391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on drive fatigue detection using wavelet transform
Driver fatigue is an important factor causing serious traffic accidents and often results in many people deaths or injuries. Therefore, many countries have made great effort on how to detect driver fatigue. This paper presents a new approach to detect driver fatigue based on discrete wavelet transform which has been used to extract the key features for constructing the classifier to identify driver fatigue. . The analyzed data are obtained from experiments using driving simulator. The result proves the algorithm is valid.