Issue No. 02 - February (2011 vol. 33)
Carlos Hernández , Google Inc., Seattle
George Vogiatzis , Aston University, Birmingham
Roberto Cipolla , University of Cambridge, Cambridge
Light occlusions are one of the most significant difficulties of photometric stereo methods. When three or more images are available without occlusion, the local surface orientation is overdetermined so that shape can be computed and the shadowed pixels can be discarded. In this paper, we look at the challenging case when only two images are available without occlusion, leading to a one degree of freedom ambiguity per pixel in the local orientation. We show that, in the presence of noise, integrability alone cannot resolve this ambiguity and reconstruct the geometry in the shadowed regions. As the problem is ill-posed in the presence of noise, we describe two regularization schemes that improve the numerical performance of the algorithm while preserving the data. Finally, the paper describes how this theory applies in the framework of color photometric stereo where one is restricted to only three images and light occlusions are common. Experiments on synthetic and real image sequences are presented.
Photometric stereo, shadows.
C. Hernández, G. Vogiatzis and R. Cipolla, "Overcoming Shadows in 3-Source Photometric Stereo," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 33, no. , pp. 419-426, 2010.