DocumentCode :
2786300
Title :
A new approach for extracting shape from texture
Author :
Cohen, Fernand S. ; Patel, Maqbool A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
fYear :
1990
fDate :
5-7 Sep 1990
Firstpage :
204
Abstract :
A novel way of modeling images that result from the projective distortions of homogeneous textures laid on illuminated 3D surfaces, as they are seen by a camera is presented. A Gaussian Markov random field (GMRF) is used for modeling the homogeneous planar parent texture. The projective distortions of the parent texture is a 2D Gaussian random field described by a probability distribution which is an explicit function of the parameters of the GMRF homogeneous texture model, the surface shape, and the camera model (orthographic or pinhole). The basic modeling concepts are used in extracting shape information from texture. Shape parameter estimation is posed as a maximum-likelihood estimation (MLE) problem
Keywords :
Markov processes; computational geometry; parameter estimation; pattern recognition; probability; Gaussian Markov random field; camera model; homogeneous textures; illuminated 3D surfaces; image modelling; maximum-likelihood estimation; orthographic camera; parameter estimation; pinhole camera; probability distribution; rojective distortions; shape extraction; surface shape; Cameras; Data mining; Light sources; Markov random fields; Maximum likelihood estimation; Parameter estimation; Probability distribution; Reflectivity; Shape; Surface texture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on
Conference_Location :
Philadelphia, PA
ISSN :
2158-9860
Print_ISBN :
0-8186-2108-7
Type :
conf
DOI :
10.1109/ISIC.1990.128459
Filename :
128459
Link To Document :
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