Unbiased Photometric Stereo for Colored Surfaces: A Variational Approach

Yvain Quéau (1) , Roberto Mecca (2) , Jean-Denis Durou (1)

1 IRIT-REVA - Real Expression Artificial Life
2 CAM - University of Cambridge [UK]

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.

Mots clés: PS; 3D color surface reconstruction; Variational approach; 3D shape recovery; Partial differential equation; Computer vision; PDE; Photometric stereo

Domaines: Synthèse d'image et réalité virtuelle [cs.GR]; Traitement du signal et de l'image [eess.SP]; Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Intelligence artificielle [cs.AI]

Yvain Quéau, Roberto Mecca, Jean-Denis Durou. Unbiased Photometric Stereo for Colored Surfaces: A Variational Approach. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2016), Jun 2016, Las Vegas, NV, United States. pp. 4359-4368. ⟨hal-01534802⟩