0391429 20240111140829.320130404235959.9 10.1007/978-3-642-37447-0_38 12 s. C cav_un_epca*0391428978-3-642-37446-30302-9743Part IV497-509BerlinSpringer Berlin Heidelberg2013 registration BTF texture material appearance multi-view cav_un_auth*0282273 Vávra Radomír Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101086 Filip Jiří Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition G Ústav teorie informace a automatizace AV ČR, v. v. i. hypertextový soubor (PDF) http://library.utia.cas.cz/separaty/2013/RO/vavra-registration of multi-view images of planar surfaces.pdf 2MB 239294 EC BE cav_un_auth*0301476 409 CESNET CZ GA102/08/0593 GA ČR cav_un_auth*0239567 GAP103/11/0335 GA ČR cav_un_auth*0273627 This paper presents a novel image-based registration method for high-resolution multi-view images of a planar material surface. Contrary to standard registration approaches, this method aligns images based on a true plane of the material's surface and not on a plane defined by registration marks. It combines the camera calibration and the iterative fitting of desired position and slant of the surface plane, image re-registration, and evaluation of the surface alignment. To optimize image compression performance, we use an error of a compression method as a function evaluating the registration quality. The proposed method shows encouraging results on example visualizations of view- and illumination-dependent textures. In addition to a standard multi-view data registration approach, it provides a better alignment of multi-view images and thus allows more detailed visualization using the same compressed parameterization size. cav_un_auth*0290443 11th Asian Conference on Computer Vision (ACCV 2012) Daejeon 05.11.2012-09.11.2012 KR 2014 BD 2 PO RVO:67985556 http://hdl.handle.net/11104/0220522 100 0.325 16.75 0.51 Q2 Q3 2013 hypertextový soubor (PDF) 2MB cav_un_epca*0391428 11th Asian Conference on Computer Vision ACCV, Revised Selected Papers Part IV 978-3-642-37446-3 0302-9743 497 509 11th Asian Conference on Computer Vision ACCV, Revised Selected Papers Berlin Springer Berlin Heidelberg 2013 Lecture Notes in Computer Science 7727