Restoring Illumination and View Dependent Data from Sparse Samples

0384216 - ÚTIA 2013 RIV US eng C - Conference Paper (international conference)
Filip, Jiří
Restoring Illumination and View Dependent Data from Sparse Samples.
Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012). Piscataway: IEEE Press, 2012, s. 1391-1394. ISBN 978-1-4673-2216-4.
[ICPR 2012 - The 21st International Conference on Pattern Recognition. Tsukuba (JP), 11.11.2012-15.11.2012]
R&D Projects: GA ČR GA102/08/0593; GA ČR GAP103/11/0335
Grant - others:CESNET(CZ) 378; CESNET(CZ) 409; Evropska komise(BE) EC Marie Curie ERG 239294
Institutional support: RVO:67985556
Keywords : reflectance measurement * BRDF reconstruction * sparse
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2012/RO/filip-restoring illumination and view dependent data from sparse samples.pdf

Capturing appearance of material with respect to illumination and viewing directions is crucial to achieve realistic visual experience in virtual environments. The capturing process is time demanding or requires a specific shape of the captured material. Therefore, we propose a method of such a data reconstruction from very sparse measurements, whose placement allows for continuous and fast acquisition, from which can benefit future acquisition setups. The proposed approach was tested on a number of view- and illumination- dependent samples and showed a promising performance in terms of whole data-space reconstruction speed and visual quality.
Permanent Link: http://hdl.handle.net/11104/0007449