{"title":"Direct methods for visual scene reconstruction","authors":"R. Szeliski, S. B. Kang","doi":"10.1109/WVRS.1995.476849","DOIUrl":null,"url":null,"abstract":"There has been a lot of activity recently surrounding the reconstruction of photorealistic 3D scenes and high-resolution images from video sequences. We present some of our recent work in this area, which is based on the registration of multiple images (views) in a projective framework. Unlike most other techniques, we do not rely on special features to form a projective basis. Instead, we directly solve a least-squares estimation problem in the unknown structure and motion parameters, which leads to statistically optimal estimates. We discuss algorithms for both constructing planar and panoramic mosaics, and for projective depth recovery. We also speculate about the ultimate usefulness of projective approaches to visual scene reconstruction.","PeriodicalId":447791,"journal":{"name":"Proceedings IEEE Workshop on Representation of Visual Scenes (In Conjunction with ICCV'95)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"136","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE Workshop on Representation of Visual Scenes (In Conjunction with ICCV'95)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WVRS.1995.476849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 136
Abstract
There has been a lot of activity recently surrounding the reconstruction of photorealistic 3D scenes and high-resolution images from video sequences. We present some of our recent work in this area, which is based on the registration of multiple images (views) in a projective framework. Unlike most other techniques, we do not rely on special features to form a projective basis. Instead, we directly solve a least-squares estimation problem in the unknown structure and motion parameters, which leads to statistically optimal estimates. We discuss algorithms for both constructing planar and panoramic mosaics, and for projective depth recovery. We also speculate about the ultimate usefulness of projective approaches to visual scene reconstruction.