{"title":"基于立体视觉的乘客座位占用率检测与分类","authors":"M. Devy, A. Giralt, A. Marín-Hernández","doi":"10.1109/IVS.2000.898433","DOIUrl":null,"url":null,"abstract":"Vision systems offer new opportunities for the improvement of vehicle safety. The detection and classification of passenger seat occupancy open up new ways to control the airbag firing. We present a stereo system designed for the observation of the cockpit scene in order to provide information about the passenger presence and location within the vehicle cockpit; from the stereo data, a cockpit occupancy map is generated. Several typical configurations of the passenger seat must be recognized (empty seat, adult presence, baby seat, ...). During an offline learning step, several cockpit images are recorded for each of these situations; for each one discriminant attributes are extracted. Then, the seat situation is recognized using a case-based classification method.","PeriodicalId":114981,"journal":{"name":"Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":"{\"title\":\"Detection and classification of passenger seat occupancy using stereovision\",\"authors\":\"M. Devy, A. Giralt, A. Marín-Hernández\",\"doi\":\"10.1109/IVS.2000.898433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vision systems offer new opportunities for the improvement of vehicle safety. The detection and classification of passenger seat occupancy open up new ways to control the airbag firing. We present a stereo system designed for the observation of the cockpit scene in order to provide information about the passenger presence and location within the vehicle cockpit; from the stereo data, a cockpit occupancy map is generated. Several typical configurations of the passenger seat must be recognized (empty seat, adult presence, baby seat, ...). During an offline learning step, several cockpit images are recorded for each of these situations; for each one discriminant attributes are extracted. Then, the seat situation is recognized using a case-based classification method.\",\"PeriodicalId\":114981,\"journal\":{\"name\":\"Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"47\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2000.898433\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2000.898433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection and classification of passenger seat occupancy using stereovision
Vision systems offer new opportunities for the improvement of vehicle safety. The detection and classification of passenger seat occupancy open up new ways to control the airbag firing. We present a stereo system designed for the observation of the cockpit scene in order to provide information about the passenger presence and location within the vehicle cockpit; from the stereo data, a cockpit occupancy map is generated. Several typical configurations of the passenger seat must be recognized (empty seat, adult presence, baby seat, ...). During an offline learning step, several cockpit images are recorded for each of these situations; for each one discriminant attributes are extracted. Then, the seat situation is recognized using a case-based classification method.