{"title":"Euclidean reconstruction from translational motion using multiple cameras","authors":"Pär Hammarstedt, A. Heyden","doi":"10.1109/3DIM.2005.36","DOIUrl":null,"url":null,"abstract":"We investigate the possibility of Euclidean reconstruction from translational motion, using multiple uncalibrated cameras. We show that in the case of multiple cameras viewing a translating scene, no additional constraints are given by the translational motion compared to the more general case with one camera viewing a scene undergoing a general motion. However, the knowledge of translational motion allows an intermediate affine reconstruction from each camera, and aids in the reconstruction process by simplifying several steps, resulting in a more reliable algorithm for 3D reconstruction. We also identify the critical directions of translation, for which no affine reconstruction is possible. Experiments on real and simulated data are performed to illustrate that the method works in practice.","PeriodicalId":170883,"journal":{"name":"Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3DIM.2005.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We investigate the possibility of Euclidean reconstruction from translational motion, using multiple uncalibrated cameras. We show that in the case of multiple cameras viewing a translating scene, no additional constraints are given by the translational motion compared to the more general case with one camera viewing a scene undergoing a general motion. However, the knowledge of translational motion allows an intermediate affine reconstruction from each camera, and aids in the reconstruction process by simplifying several steps, resulting in a more reliable algorithm for 3D reconstruction. We also identify the critical directions of translation, for which no affine reconstruction is possible. Experiments on real and simulated data are performed to illustrate that the method works in practice.