{"title":"Concentric mosaic(s), planar motion and 1D cameras","authors":"Long Quan, Le Lu, H. Shum, M. Lhuillier","doi":"10.1109/ICCV.2001.937624","DOIUrl":null,"url":null,"abstract":"General SFM methods give poor results for images captured by constrained motions such as planar motion of concentric mosaics (CM). In this paper we propose new SFM algorithms for both images captured by CM and composite mosaic images from CM. We first introduce ID affine camera model for completing 1D camera models. Then we show that a 2D image captured by CM can be decoupled into two 1D images: one 1D projective and one ID affine; a composite mosaic image can by rebinned into a calibrated ID panorama projective camera. Finally we describe subspace reconstruction methods and demonstrate both in theory and experiments the advantage of the decomposition method over the general SFM methods by incorporating the constrained motion into the earliest stage of motion analysis.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"341 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2001.937624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
General SFM methods give poor results for images captured by constrained motions such as planar motion of concentric mosaics (CM). In this paper we propose new SFM algorithms for both images captured by CM and composite mosaic images from CM. We first introduce ID affine camera model for completing 1D camera models. Then we show that a 2D image captured by CM can be decoupled into two 1D images: one 1D projective and one ID affine; a composite mosaic image can by rebinned into a calibrated ID panorama projective camera. Finally we describe subspace reconstruction methods and demonstrate both in theory and experiments the advantage of the decomposition method over the general SFM methods by incorporating the constrained motion into the earliest stage of motion analysis.