0565332 - ÚTIA 2023 RIV CH eng C - Conference Paper (international conference)
Haindl, Michal - Havlíček, Vojtěch
BRDF Anisotropy Criterion.
Intelligent Information and Database Systems. Cham: Springer Nature, 2022 - (Nguyen, N.; Tran, T.; Tukayev, U.; Hong, T.; Trawinski, B.; Szczerbicki, E.), s. 434-444. Lecture Notes in Artificial Intelligence, 13758. ISBN 978-3-031-21966-5. ISSN 0302-9743. E-ISSN 1611-3349.
[Asian Conference on Intelligent Information and Database Systems (ACIIDS 2022) /14./. Ho Chi Minh City (VN), 28.11.2022-30.11.2022]
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : BRDF modeling * anisotropy criterion * hyperspectral BRDF
OECD category: Automation and control systems
Result website:
http://library.utia.cas.cz/separaty/2022/RO/haindl-0565332.pdf

DOI: https://doi.org/10.1007/978-3-031-21967-2_35

Visual scene recognition is predominantly based on visual textures representing an object's material properties. However, the single material texture varies in scale and illumination angles due to mapping an object's shape. We present an anisotropy criterion of bidirectional reflectance distribution function (BRDF), which allows deciding if a simpler isotropic BRDF model can be used or if it is necessary to use a more complex anisotropic BRDF model. The criterion simultaneously shows dominant angular orientations for the anisotropic materials. The anisotropic criterion is tested on several isotropic and anisotropic surface materials, with BRDF computed from the measured seven-dimensional Bidirectional Texture Function.
Permanent Link: https://hdl.handle.net/11104/0337888