Fourier Analysis and Gabor Filtering for Texture Analysis and Local Reconstruction of General Shapes
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.
Cite
Text
Galasso and Lasenby. "Fourier Analysis and Gabor Filtering for Texture Analysis and Local Reconstruction of General Shapes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009. doi:10.1109/CVPR.2009.5206591Markdown
[Galasso and Lasenby. "Fourier Analysis and Gabor Filtering for Texture Analysis and Local Reconstruction of General Shapes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009.](https://mlanthology.org/cvpr/2009/galasso2009cvpr-fourier/) doi:10.1109/CVPR.2009.5206591BibTeX
@inproceedings{galasso2009cvpr-fourier,
title = {{Fourier Analysis and Gabor Filtering for Texture Analysis and Local Reconstruction of General Shapes}},
author = {Galasso, Fabio and Lasenby, Joan},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2009},
pages = {2342-2349},
doi = {10.1109/CVPR.2009.5206591},
url = {https://mlanthology.org/cvpr/2009/galasso2009cvpr-fourier/}
}