Solving Uncalibrated Photometric Stereo using Total Variation

Yvain Quéau (1) , François Lauze (2) , Jean-Denis Durou (1)

1 IRIT-REVA - Real Expression Artificial Life
2 UCPH - University of Copenhagen = Københavns Universitet

Estimating the shape and appearance of an object, given one or several images, is still an open and challenging research problem called 3D-reconstruction. Among the different techniques available, photometric stereo (PS) produces highly accurate results when the lighting conditions have been identified. When these conditions are unknown, the problem becomes the so-called uncalibrated PS problem, which is ill-posed. In this paper, we will show how total variation can be used to reduce the ambiguities of uncalibrated PS, and we will study two methods for estimating the parameters of the generalized bas-relief ambiguity. These methods will be evaluated through the 3D-reconstruction of real-world objects.

Mots clés: 3D-reconstruction; Photometric stereo; Total variation; Generalized bas-relief ambiguity

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, François Lauze, Jean-Denis Durou. Solving Uncalibrated Photometric Stereo using Total Variation. Journal of Mathematical Imaging and Vision, 2015, vol. 52 (n° 1), pp. 87-107. ⟨10.1007/s10851-014-0512-5⟩. ⟨hal-01360868⟩