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Unbiased Photometric Stereo for Colored Surfaces: A Variational Approach

Accepted version
Peer-reviewed

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Type

Article

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Authors

Quéau, Yvain 
Mecca, Roberto 
Durou, Jean-Denis 

Abstract

3D shape recovery using photometric stereo (PS) gained increasing attention in the computer vision community in the last three decades due to its ability to recover the thinnest geometric structures. Yet, the reliability of PS for color images is difficult to guarantee, because existing methods are usually formulated as the sequential estimation of the colored albedos, the normals and the depth. Hence, the overall reliability depends on that of each subtask. In this work we propose a new formulation of color photometric stereo, based on image ratios, that makes the technique independent from the albedos. This allows the unbiased 3D- reconstruction of colored surfaces in a single step, by solving a system of linear PDEs using a variational approach.

Description

This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by IEEE.

Keywords

46 Information and Computing Sciences, 4607 Graphics, Augmented Reality and Games, 40 Engineering, 4603 Computer Vision and Multimedia Computation

Journal Title

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Conference Name

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Journal ISSN

Volume Title

Publisher

IEEE