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