复杂建筑物的多幅图像自动描述

Z. Kim, A. Huertas, R. Nevatia
{"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}
引用次数: 113

摘要

三维建筑物检测与描述是三维物体描述的实际应用,是计算机视觉的一项关键任务。我们提出了一种通过使用场景的多个重叠图像来检测和描述多边形屋顶建筑的方法。首先,利用多幅图像生成三维特征,并通过对这些特征的邻域搜索生成屋顶假设。为了鲁棒生成三维特征,我们提出了一种概率方法来解决线匹配中的极线对齐问题。图像衍生的未经编辑的高程数据用于辅助特征匹配,并生成三维结构存在的粗略线索。这些线索有助于显著减少搜索空间。在一些复杂的建筑物上给出了实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信