{"title":"基于反向时序处理的驾驶视频分析","authors":"F. Maire, A. Rakotonirainy","doi":"10.1109/CGIV.2006.21","DOIUrl":null,"url":null,"abstract":"Technology based driver training is still in its infancy. There is a strong need for improved and integrated computer-based screening tools in order to facilitate objective and reliable driver training assessments. This paper describes a system that analyses videos of driving sessions collected by on-board Web-cameras. The system detects and tracks lane markings in order to estimate the relative position of the vehicle with respect to its lane. The system is computationally efficient as it exploits fully the off-line nature of the data. The analysis of the video recording is performed in reverse temporal order. The benefits of this approach compared to the forward analysis traditionally used are an improved robustness and a lower computational cost","PeriodicalId":264596,"journal":{"name":"International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analysis of Driving Session Videos by Reverse Temporal Order Processing\",\"authors\":\"F. Maire, A. Rakotonirainy\",\"doi\":\"10.1109/CGIV.2006.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Technology based driver training is still in its infancy. There is a strong need for improved and integrated computer-based screening tools in order to facilitate objective and reliable driver training assessments. This paper describes a system that analyses videos of driving sessions collected by on-board Web-cameras. The system detects and tracks lane markings in order to estimate the relative position of the vehicle with respect to its lane. The system is computationally efficient as it exploits fully the off-line nature of the data. The analysis of the video recording is performed in reverse temporal order. The benefits of this approach compared to the forward analysis traditionally used are an improved robustness and a lower computational cost\",\"PeriodicalId\":264596,\"journal\":{\"name\":\"International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CGIV.2006.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGIV.2006.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Driving Session Videos by Reverse Temporal Order Processing
Technology based driver training is still in its infancy. There is a strong need for improved and integrated computer-based screening tools in order to facilitate objective and reliable driver training assessments. This paper describes a system that analyses videos of driving sessions collected by on-board Web-cameras. The system detects and tracks lane markings in order to estimate the relative position of the vehicle with respect to its lane. The system is computationally efficient as it exploits fully the off-line nature of the data. The analysis of the video recording is performed in reverse temporal order. The benefits of this approach compared to the forward analysis traditionally used are an improved robustness and a lower computational cost