{"title":"复杂建筑物的多幅图像自动描述","authors":"Z. Kim, A. Huertas, R. Nevatia","doi":"10.1109/WACV.2000.895417","DOIUrl":null,"url":null,"abstract":"3-D building detection and description is a practical application of 3-D object description, a key task of computer vision. We present an approach to detecting and describing buildings of polygonal rooftops by using multiple, overlapping images of the scene. First, 3-D features are generated by using multiple images, and rooftop hypotheses are generated by neighborhood searches on those features. For robust generation of 3-D features, we present a probabilistic approach to address the epipolar alignment problem in line matching. Image-derived unedited elevation data is used to assist feature matching, and to generate rough cues of the presence of 3-D structures. These cues help reduce the search space significantly. Experimental results are shown on some complex buildings.","PeriodicalId":306720,"journal":{"name":"Proceedings Fifth IEEE Workshop on Applications of Computer Vision","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"113","resultStr":"{\"title\":\"Automatic description of complex buildings with multiple images\",\"authors\":\"Z. Kim, A. Huertas, R. Nevatia\",\"doi\":\"10.1109/WACV.2000.895417\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"3-D building detection and description is a practical application of 3-D object description, a key task of computer vision. We present an approach to detecting and describing buildings of polygonal rooftops by using multiple, overlapping images of the scene. First, 3-D features are generated by using multiple images, and rooftop hypotheses are generated by neighborhood searches on those features. For robust generation of 3-D features, we present a probabilistic approach to address the epipolar alignment problem in line matching. Image-derived unedited elevation data is used to assist feature matching, and to generate rough cues of the presence of 3-D structures. These cues help reduce the search space significantly. Experimental results are shown on some complex buildings.\",\"PeriodicalId\":306720,\"journal\":{\"name\":\"Proceedings Fifth IEEE Workshop on Applications of Computer Vision\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"113\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Fifth IEEE Workshop on Applications of Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WACV.2000.895417\",\"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 Fifth IEEE Workshop on Applications of Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WACV.2000.895417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic description of complex buildings with multiple images
3-D building detection and description is a practical application of 3-D object description, a key task of computer vision. We present an approach to detecting and describing buildings of polygonal rooftops by using multiple, overlapping images of the scene. First, 3-D features are generated by using multiple images, and rooftop hypotheses are generated by neighborhood searches on those features. For robust generation of 3-D features, we present a probabilistic approach to address the epipolar alignment problem in line matching. Image-derived unedited elevation data is used to assist feature matching, and to generate rough cues of the presence of 3-D structures. These cues help reduce the search space significantly. Experimental results are shown on some complex buildings.