2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '03) - Volume 1
3D Shape from Anisotropic Diffusion
Madison, Wisconsin
June 18-June 20
ISBN: 0-7695-1900-8
We cast the problem of inferring 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 inferring the diffusion coefficient of a heat equation. The method is optimal, as we pose it as the minimization of a certain 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.
Index Terms:
shape from defocus, depth from defocus, early vision, image-based modeling, shape representation, anisotropic diffusion
Citation:
P. Favaro, S. Osher, S. Soatto, L. Vese, "3D Shape from Anisotropic Diffusion," cvpr, vol. 1, pp.179, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '03) - Volume 1, 2003