3D shape from anisotropic diffusion

Authors:
P. Favaro;S. Osher;S. Soatto;L. Vese
Affiliations:
Dept. of Electrical Engineering, Washington University, St. Louis, MO;Dept. of Applied Mathematics, UCLA, Los Angeles, CA;Dept. of Computer Science, UCLA, Los Angeles, CA;Dept. of Applied Mathematics, UCLA, Los Angeles, CA
Venue:
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Year:
2003

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Abstract

We cast the problem of iriferring the 3D shape of a scene from a collection of defocused images in the framework of anisotropic diffusion. We propose a novel algorithm that can estimate the shape of a scene by iriferring the diffusion coefficient of a heat equation. The method is optimal, as we pose it as the minimization of a cenain cost functional based on the input images, and fast. Furthermore, we also extend our algorithm to the case of multiple images, and derive a 3D scene segmentation algorithm that can work in the presence of pictorial camouflage.