Three-dimensional Gaussian Mixture Texture Model

0467541 - ÚTIA 2017 RIV US eng C - Conference Paper (international conference)
Haindl, Michal - Havlíček, Vojtěch
Three-dimensional Gaussian Mixture Texture Model.
Proceedings of the 23rd International Conference on Pattern Recognition (ICPR). Piscataway: IEEE, 2016, s. 2026-2031, č. článku 1003. ISBN 978-1-5090-4846-5.
[23rd International Conference on Pattern Recognition ICPR 2016. Cancún (MX), 04.12.2016-08.12.2016]
R&D Projects: GA ČR(CZ) GA14-10911S
Institutional support: RVO:67985556
Keywords : bidirectional texture function * Gaussian mixture model * texture modeling
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2016/RO/haindl-0467541.pdf

Visual texture modeling based on multidimensional mathematical models is the prerequisite for both robust material recognition as well as for image restoration, compression or numerous physically correct virtual reality applications. A novel multispectral visual texture modeling method based on a descriptive, unusually complex, three-dimensional, spatial Gaussian mixture model is presented. Texture synthesis benefits from easy computation of arbitrary conditional distributions from the model. The model is inherently multispectral thus it does not suffer with the spectral quality compromises of the spectrally factorized alternative approaches. The model is especially well suited for multispectral textile textures and it can also describe the most advanced textural representation in the form of a bidirectional texture function (BTF).
Permanent Link: http://hdl.handle.net/11104/0266451