{"title":"A quasi linear reconstruction method from multiple perspective views","authors":"S. Christy, R. Horaud","doi":"10.1109/IROS.1995.526244","DOIUrl":null,"url":null,"abstract":"In this paper we describe a method for solving the Euclidean reconstruction problem with a perspective camera model by incrementally performing an Euclidean reconstruction with a weak perspective camera model. With respect to other methods that compute shape and motion from a sequence of images with a calibrated perspective camera, this method converges in a few iterations, is compositionally efficient, and does not suffer from the nonlinear nature of the problem. With respect to factorization and/or affine-invariant methods, this method solves for the sign (reversal) ambiguity in a very simple way and provides much more accurate reconstructions results.","PeriodicalId":124483,"journal":{"name":"Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots","volume":"228 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1995.526244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper we describe a method for solving the Euclidean reconstruction problem with a perspective camera model by incrementally performing an Euclidean reconstruction with a weak perspective camera model. With respect to other methods that compute shape and motion from a sequence of images with a calibrated perspective camera, this method converges in a few iterations, is compositionally efficient, and does not suffer from the nonlinear nature of the problem. With respect to factorization and/or affine-invariant methods, this method solves for the sign (reversal) ambiguity in a very simple way and provides much more accurate reconstructions results.