Near-Regular BTF Texture Model

0346563 - ÚTIA 2011 RIV US eng C - Conference Paper (international conference)
Haindl, Michal - Hatka, Martin
Near-Regular BTF Texture Model.
20th International Conference on Pattern Recognition. Los Alamitos: IEEE Computer Society CPS, 2010, s. 2114-2117. ISBN 978-1-4244-7542-1. ISSN 1051-4651.
[20th International Conference on Pattern Recognition ICPR 2010. Istanbul (TR), 23.08.2010-26.08.2010]
R&D Projects: GA MŠMT 1M0572; GA ČR GA102/08/0593
Grant - others:GA MŠk(CZ) 2C06019
Institutional research plan: CEZ:AV0Z10750506
Keywords : near-regular texture * texture editing * Markov random field * bidirectional texture function
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2010/RO/haindl-near-regular btf texture model.pdf

In this paper we present a method for seamless enlargement and editing of intricate near-regular type of bidirectional texture function (BTF) which contains simultaneously both regular periodic and stochastic components. Such BTF textures cannot be convincingly synthesised using neither simple tiling nor using purely stochastic models. However these textures are ubiquitous in many man-made environments and also in some natural scenes. Thus they are required for their realistic appearance visualisation. The principle of the presented BTF-NR synthesis and editing method is to automatically separate periodic and random components from one or more input textures. Each of these components is subsequently independently modelled using its corresponding optimal method. The regular texture part is modelled using our roller method, while the random part is synthesised from its estimated exceptionally efficient Markov random field based representation.
Permanent Link: http://hdl.handle.net/11104/0187563