A Psychophysical Evaluation of Texture Degradation Descriptors

0346556 - ÚTIA 2011 RIV DE eng C - Conference Paper (international conference)
Filip, Jiří - Vácha, Pavel - Haindl, Michal - Green, P.R.
A Psychophysical Evaluation of Texture Degradation Descriptors.
Structural, Syntactic, and Statistical Pattern Recognition. Berlin / Heidelberg: Springer Berlin / Heidelberg, 2010 - (Hancock, Edwin and Wilson, Richard and Windeatt, Terry and Ulusoy, Ilkay and Escolano, Francisco), s. 423-433. LNCS, 6218. ISBN 978-3-642-14979-5. ISSN 0302-9743.
[Structural, Syntactic, and Statistical Pattern Recognition. Cesme, Izmir (TR), 18.08.2010-20.08.2010]
R&D Projects: GA MŠMT 1M0572; GA ČR GA102/08/0593
Grant - others:EC Marie Curie(BE) ERG 239294
Institutional research plan: CEZ:AV0Z10750506
Keywords : texture * degradation * statistical features * BTF * psychophysics
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2010/RO/filip-a psychophysical evaluation of texture degradation descriptors.pdf

Delivering a digital realistic appearance of materials is one of the most difficult tasks of computer vision. Accurate representation of surface texture can be obtained by means of view and illumination dependent textures. However, this kind of appearance representation produces massive datasets so their compression is inevitable. For optimal visual performance of compression methods, their parameters should be set dependently on the actual material. We propose a set of statistical descriptors motivated by standard textural features, and psychophysically evaluate their performance on three subtle artificial texture visual degradations. We tested the five types of descriptors on five different textures and combination of thirteen surface shapes and two illuminations. We have found that descriptors based on two-dimensional causal auto-regressive model, have the highest correlation with the psychophysical results.
Permanent Link: http://hdl.handle.net/11104/0187557