bibtype C - Conference Paper (international conference)
ARLID 0369913
utime 20240103200119.7
mtime 20120110235959.9
title (primary) (eng) Advanced textural representation of materials appearance
specification
page_count 84 s.
serial
ARLID cav_un_epca*0370977
ISBN 978-1-4503-1135-9
title Proceedings of SA '11 SIGGRAPH Asia 2011 Courses
page_num 1-84
publisher
place New York
name ACM
year 2011
editor
name1 Sander
name2 P.
keyword visual texture
keyword Bidirectional Texture Function
keyword materials appearance
author (primary)
ARLID cav_un_auth*0101093
name1 Haindl
name2 Michal
full_dept (cz) Rozpoznávání obrazu
full_dept (eng) Department of Pattern Recognition
department (cz) RO
department (eng) RO
institution UTIA-B
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101086
name1 Filip
name2 Jiří
full_dept (cz) Rozpoznávání obrazu
full_dept Department of Pattern Recognition
department (cz) RO
department RO
institution UTIA-B
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2012/RO/haindl-advanced textural representation of materials appearance.pdf
cas_special
project
project_id 387/2010
agency CESNET
country CZ
project
project_id GA102/08/0593
agency GA ČR
ARLID cav_un_auth*0239567
project
project_id GAP103/11/0335
agency GA ČR
ARLID cav_un_auth*0273627
research CEZ:AV0Z10750506
abstract (eng) Multidimensional visual texture is the appropriate paradigm for physically correct material visual properties representation. The course will present recent advances in texture modelling methodology as applied in computer vision, pattern recognition, computer graphics, and virtual/augmented reality applications. Contrary to previous courses on material appearance, we will focus on materials whose nature allows the exploitation of texture modeling approaches. This topic is introduced in the wider and complete context of pattern recognition and image rocessing. It comprehends modeling of multi-spectral images and videos which can be accomplished either with multi-dimensional mathematical models or sophisticated sampling methods from the original measurements. The key aspects of the topic, i.e., different multi-dimensional data models with their corresponding benefits and drawbacks, optimal model selection, parameter estimation and model synthesis techniques, are discussed.
action
ARLID cav_un_auth*0277647
name SIGGRAPH Asia 2011
place Hong Kong
dates 12.12.2011-15.12.2011
country CN
reportyear 2012
RIV BD
num_of_auth 2
permalink http://hdl.handle.net/11104/0203864
arlyear 2011
mrcbU63 cav_un_epca*0370977 Proceedings of SA '11 SIGGRAPH Asia 2011 Courses 978-1-4503-1135-9 1 84 New York ACM 2011
mrcbU67 Sander P. 340