A scale space for texture+depth images based on a discrete Laplacian operator - Archive ouverte HAL
Communication Dans Un Congrès Année : 2015

A scale space for texture+depth images based on a discrete Laplacian operator

Résumé

In this paper we design a smoothing filter for texture+depth images based on anisotropic diffusion. Our proposed filter enables to generate a scale space on the texture image guided by depth information , and is linear and numerically stable. We show experimentally that using scene geometry preserves the internal structure of 3D surfaces (e.g., it avoids smoothing across object boundaries). As a consequence, the result of smoothing is more independent to changes in the camera position. To illustrate the practical utility of a scale space with such properties, we integrate our filter into the SIFT key-point detector, getting a substantial improvement of the repeatability of detected keypoints under significant viewpoint position changes.
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Dates et versions

hal-01299841 , version 1 (08-04-2016)

Identifiants

Citer

Maxim Karpushin, Giuseppe Valenzise, Frédéric Dufaux. A scale space for texture+depth images based on a discrete Laplacian operator. IEEE International Conference on Multimedia and Expo, Jun 2015, Turin, Italy. ⟨10.1109/ICME.2015.7177500⟩. ⟨hal-01299841⟩
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