T. Aizawa, A. Tanaka, H. Higashikage, Y. Asokawa, M. Kimachi, S. Ogata
{"title":"基于立体车辆检测的路面估计鲁棒性","authors":"T. Aizawa, A. Tanaka, H. Higashikage, Y. Asokawa, M. Kimachi, S. Ogata","doi":"10.1109/ITSC.2002.1041186","DOIUrl":null,"url":null,"abstract":"In parameters estimation for stereo-based vehicle detection, it is important to estimate the three-dimensional geometrical relationship between a stereo camera and a road surface. However, vehicles' existence in a field of view sometimes has a bad influence upon the accuracy of road surface estimation. Therefore, we propose a method for road surface estimation robust against vehicles' existence in a field of view. This method considers the difference between the distribution of feature points from a road surface and those from a vehicle in the spatio-disparity space. Therefore, road surface estimation can be done using those mostly from a road surface. We also confirm its effectiveness by experiments on field images.","PeriodicalId":365722,"journal":{"name":"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Road surface estimation robust against vehicles' existence for stereo-based vehicle detection\",\"authors\":\"T. Aizawa, A. Tanaka, H. Higashikage, Y. Asokawa, M. Kimachi, S. Ogata\",\"doi\":\"10.1109/ITSC.2002.1041186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In parameters estimation for stereo-based vehicle detection, it is important to estimate the three-dimensional geometrical relationship between a stereo camera and a road surface. However, vehicles' existence in a field of view sometimes has a bad influence upon the accuracy of road surface estimation. Therefore, we propose a method for road surface estimation robust against vehicles' existence in a field of view. This method considers the difference between the distribution of feature points from a road surface and those from a vehicle in the spatio-disparity space. Therefore, road surface estimation can be done using those mostly from a road surface. We also confirm its effectiveness by experiments on field images.\",\"PeriodicalId\":365722,\"journal\":{\"name\":\"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2002.1041186\",\"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. The IEEE 5th International Conference on Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2002.1041186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Road surface estimation robust against vehicles' existence for stereo-based vehicle detection
In parameters estimation for stereo-based vehicle detection, it is important to estimate the three-dimensional geometrical relationship between a stereo camera and a road surface. However, vehicles' existence in a field of view sometimes has a bad influence upon the accuracy of road surface estimation. Therefore, we propose a method for road surface estimation robust against vehicles' existence in a field of view. This method considers the difference between the distribution of feature points from a road surface and those from a vehicle in the spatio-disparity space. Therefore, road surface estimation can be done using those mostly from a road surface. We also confirm its effectiveness by experiments on field images.