{"title":"城市环境下自动驾驶汽车导航的精确特征匹配","authors":"J. Sasiadek, M. Walker, A. Krzyżak","doi":"10.1109/MMAR.2011.6031318","DOIUrl":null,"url":null,"abstract":"The research presented in this paper ultimately aims at accurate Unmanned Aerial Vehicle (UAV) navigation using camera(s) to augment inertial navigation unit data while flying through an urban environment. Accurate position and depth determination requires precise image feature location and matching. This paper investigates accurate feature matching enabling determination of image depth. The paper offers two unique contributions to the field. First, it is shown how to improve feature matching accuracy when a good position estimate is available. Secondly, it is shown how to increase the number of matched features. In this way, there is more data and it may be possible, in future research, to identify the depth plane a feature belongs to and so increase the accuracy of position determination. Preliminary results are reported.","PeriodicalId":440376,"journal":{"name":"2011 16th International Conference on Methods & Models in Automation & Robotics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Accurate feature matching for autonomous vehicle navigation in urban environments\",\"authors\":\"J. Sasiadek, M. Walker, A. Krzyżak\",\"doi\":\"10.1109/MMAR.2011.6031318\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research presented in this paper ultimately aims at accurate Unmanned Aerial Vehicle (UAV) navigation using camera(s) to augment inertial navigation unit data while flying through an urban environment. Accurate position and depth determination requires precise image feature location and matching. This paper investigates accurate feature matching enabling determination of image depth. The paper offers two unique contributions to the field. First, it is shown how to improve feature matching accuracy when a good position estimate is available. Secondly, it is shown how to increase the number of matched features. In this way, there is more data and it may be possible, in future research, to identify the depth plane a feature belongs to and so increase the accuracy of position determination. Preliminary results are reported.\",\"PeriodicalId\":440376,\"journal\":{\"name\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMAR.2011.6031318\",\"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 16th International Conference on Methods & Models in Automation & Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2011.6031318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Accurate feature matching for autonomous vehicle navigation in urban environments
The research presented in this paper ultimately aims at accurate Unmanned Aerial Vehicle (UAV) navigation using camera(s) to augment inertial navigation unit data while flying through an urban environment. Accurate position and depth determination requires precise image feature location and matching. This paper investigates accurate feature matching enabling determination of image depth. The paper offers two unique contributions to the field. First, it is shown how to improve feature matching accuracy when a good position estimate is available. Secondly, it is shown how to increase the number of matched features. In this way, there is more data and it may be possible, in future research, to identify the depth plane a feature belongs to and so increase the accuracy of position determination. Preliminary results are reported.