Institute of Information Theory and Automation

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Publication details

Restoring Illumination and View Dependent Data from Sparse Samples

Conference Paper (international conference)

Filip Jiří

serial: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), p. 1391-1394

action: ICPR 2012 - The 21st International Conference on Pattern Recognition, (Tsukuba, JP, 11.11.2012-15.11.2012)

project(s): GA102/08/0593, GA ČR, 378, CESNET, 409, CESNET, EC Marie Curie ERG 239294, Evropska komise, GAP103/11/0335, GA ČR

keywords: reflectance measurement, BRDF reconstruction, sparse

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abstract (eng):

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.


2012-12-21 16:10