Title :
Fourier analysis and Gabor filtering for texture analysis and local reconstruction of general shapes
Author :
Galasso, Fabio ; Lasenby, Joan
Author_Institution :
Univ. of Cambridge, Cambridge, UK
Abstract :
Since the pioneering work of Gibson in 1950, Shape-From-Texture has been considered by researchers as a hard problem, mainly due to restrictive assumptions which often limit its applicability. We assume a very general stochastic homogeneity and perspective camera model, for both deterministic and stochastic textures. A multi-scale distortion is efficiently estimated with a previously presented method based on Fourier analysis and Gabor filters. The novel 3D reconstruction method that we propose applies to general shapes, and includes non-developable and extensive surfaces. Our algorithm is accurate, robust and compares favorably to the present state of the art of Shape-From-Texture. Results show its application to non-invasively study shape changes with laid-on textures, while rendering and re-texturing of cloth is suggested for future work.
Keywords :
Fourier analysis; Gabor filters; image reconstruction; image texture; 3D reconstruction; Fourier analysis; Gabor filtering; Gabor filters; deterministic textures; general shapes; hard problem; local reconstruction; multiscale distortion; perspective camera model; shape-from-texture; stochastic homogeneity; stochastic textures; texture analysis; Cameras; Distortion measurement; Filtering; Frequency estimation; Gabor filters; Image reconstruction; Robustness; Shape; Stochastic processes; Surface reconstruction;
Conference_Titel :
Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-3992-8
DOI :
10.1109/CVPR.2009.5206591