{"title":"探测人造建筑鸟瞰图的变化","authors":"A. Huertas, R. Nevatia","doi":"10.1109/ICCV.1998.710703","DOIUrl":null,"url":null,"abstract":"Many applications require detecting structural changes in a scene over a period of time. Comparing intensity values of successive images is not effective as such changes don't necessarily reflect actual changes at a site but might be caused by changes in the view point, illumination and seasons. We take the approach of comparing a 3-D model of the site, prepared from previous images, with new images to infer significant changes. This task is difficult as the images and the models have very different levels of abstract representations. Our approach consists of several steps: registering a site model to a new image, model validation to confirm the presence of model objects in the image; structural change detection seeks to resolve matching problems and indicate possibly changed structures; and finally updating models to reflect the changes. Our system is able to detect missing (or mis-modeled) buildings, changes in model dimensions, and new buildings under some conditions.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"25 1-2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"116","resultStr":"{\"title\":\"Detecting changes in aerial views of man-made structures\",\"authors\":\"A. Huertas, R. Nevatia\",\"doi\":\"10.1109/ICCV.1998.710703\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many applications require detecting structural changes in a scene over a period of time. Comparing intensity values of successive images is not effective as such changes don't necessarily reflect actual changes at a site but might be caused by changes in the view point, illumination and seasons. We take the approach of comparing a 3-D model of the site, prepared from previous images, with new images to infer significant changes. This task is difficult as the images and the models have very different levels of abstract representations. Our approach consists of several steps: registering a site model to a new image, model validation to confirm the presence of model objects in the image; structural change detection seeks to resolve matching problems and indicate possibly changed structures; and finally updating models to reflect the changes. Our system is able to detect missing (or mis-modeled) buildings, changes in model dimensions, and new buildings under some conditions.\",\"PeriodicalId\":270671,\"journal\":{\"name\":\"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)\",\"volume\":\"25 1-2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-01-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"116\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCV.1998.710703\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.1998.710703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detecting changes in aerial views of man-made structures
Many applications require detecting structural changes in a scene over a period of time. Comparing intensity values of successive images is not effective as such changes don't necessarily reflect actual changes at a site but might be caused by changes in the view point, illumination and seasons. We take the approach of comparing a 3-D model of the site, prepared from previous images, with new images to infer significant changes. This task is difficult as the images and the models have very different levels of abstract representations. Our approach consists of several steps: registering a site model to a new image, model validation to confirm the presence of model objects in the image; structural change detection seeks to resolve matching problems and indicate possibly changed structures; and finally updating models to reflect the changes. Our system is able to detect missing (or mis-modeled) buildings, changes in model dimensions, and new buildings under some conditions.