{"title":"在c速度空间中“免费”进行障碍物检测","authors":"S. Bouchafa, B. Zavidovique","doi":"10.1109/ITSC.2011.6082872","DOIUrl":null,"url":null,"abstract":"Obstacle detection is a key process of automatic driver assistance. The present paper focuses on ”vision”, and particularly on ”monocular” mobile vision, to reconstruct a rough Scene-Structure From Motion. Considering the 3D scene as a set of 3D planes, our c-velocity approach segments the optical flow field into plane pieces without any camera calibration or a priori knowledge about the egomotion. The technical tip is to exhibit iso-velocity curves in establishing relations between their properties and plane orientations. We show in this paper how obstacle detection becomes obvious, costless and robust with the method. Results confirm the expected robustness, not to forget that the method extends to other parameterized surfaces.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Obstacle detection ”for free” in the c-velocity space\",\"authors\":\"S. Bouchafa, B. Zavidovique\",\"doi\":\"10.1109/ITSC.2011.6082872\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Obstacle detection is a key process of automatic driver assistance. The present paper focuses on ”vision”, and particularly on ”monocular” mobile vision, to reconstruct a rough Scene-Structure From Motion. Considering the 3D scene as a set of 3D planes, our c-velocity approach segments the optical flow field into plane pieces without any camera calibration or a priori knowledge about the egomotion. The technical tip is to exhibit iso-velocity curves in establishing relations between their properties and plane orientations. We show in this paper how obstacle detection becomes obvious, costless and robust with the method. Results confirm the expected robustness, not to forget that the method extends to other parameterized surfaces.\",\"PeriodicalId\":186596,\"journal\":{\"name\":\"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2011.6082872\",\"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 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2011.6082872","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Obstacle detection ”for free” in the c-velocity space
Obstacle detection is a key process of automatic driver assistance. The present paper focuses on ”vision”, and particularly on ”monocular” mobile vision, to reconstruct a rough Scene-Structure From Motion. Considering the 3D scene as a set of 3D planes, our c-velocity approach segments the optical flow field into plane pieces without any camera calibration or a priori knowledge about the egomotion. The technical tip is to exhibit iso-velocity curves in establishing relations between their properties and plane orientations. We show in this paper how obstacle detection becomes obvious, costless and robust with the method. Results confirm the expected robustness, not to forget that the method extends to other parameterized surfaces.