{"title":"基于眼睛和头部状态的驾驶员入睡检测算法","authors":"P. N. Huu, Trang Pham Thi Thu","doi":"10.1109/NICS54270.2021.9701503","DOIUrl":null,"url":null,"abstract":"In the paper, we present an algorithm for detecting driver drowsiness based on computer vision techniques. The algorithm will issue a warning signal when drivers are dozing based on the state of eyes closing as well as the tilt of the head with a camera used to observe their faces. The proposed method determines six landmarks of eyes to detect eye closure and binocular coordinates to calculate head tilt angle. The results show that the proposed algorithm achieves an accuracy of up to 95.25% with 16 frames per second. The results show that the algorithm is suitable for development in real applications.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detecting Drivers Falling Asleep Algorithm Based on Eye and Head States\",\"authors\":\"P. N. Huu, Trang Pham Thi Thu\",\"doi\":\"10.1109/NICS54270.2021.9701503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the paper, we present an algorithm for detecting driver drowsiness based on computer vision techniques. The algorithm will issue a warning signal when drivers are dozing based on the state of eyes closing as well as the tilt of the head with a camera used to observe their faces. The proposed method determines six landmarks of eyes to detect eye closure and binocular coordinates to calculate head tilt angle. The results show that the proposed algorithm achieves an accuracy of up to 95.25% with 16 frames per second. The results show that the algorithm is suitable for development in real applications.\",\"PeriodicalId\":296963,\"journal\":{\"name\":\"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NICS54270.2021.9701503\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NICS54270.2021.9701503","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detecting Drivers Falling Asleep Algorithm Based on Eye and Head States
In the paper, we present an algorithm for detecting driver drowsiness based on computer vision techniques. The algorithm will issue a warning signal when drivers are dozing based on the state of eyes closing as well as the tilt of the head with a camera used to observe their faces. The proposed method determines six landmarks of eyes to detect eye closure and binocular coordinates to calculate head tilt angle. The results show that the proposed algorithm achieves an accuracy of up to 95.25% with 16 frames per second. The results show that the algorithm is suitable for development in real applications.