Title
Resolving the Generalized Bas-Relief Ambiguity by Entropy Minimization
Abstract
It is well known in the photometric stereo literature that uncalibrated photometric stereo, where light source strength and direction are unknown, can recover the surface geometry of a Lambertian object up to a 3-parameter linear transform known as the generalized bas relief (GBR) ambi- guity. Many techniques have been proposed for resolving the GBR ambiguity, typically by exploiting prior knowledge of the light sources, the object geometry, or non-Lambertian effects such as specularities. A less celebrated consequence of the GBR transformation is that the albedo at each sur- face point is transformed along with the geometry. Thus, it should be possible to resolve the GBR ambiguity by ex- ploiting priors on the albedo distribution. To the best of our knowledge, the only time the albedo distribution has been used to resolve the GBR is in the case of uniform albedo. We propose a new prior on the albedo distribution : that the entropy of the distribution should be low. This prior is justified by the fact that many objects in the real-world are composed of a small finite set of albedo values.
Year
DOI
Venue
2007
10.1109/CVPR.2007.383208
CVPR
Keywords
Field
DocType
computational geometry,computer vision,inference mechanisms,minimisation,statistical distributions,stereo image processing,GBR ambiguity,GBR transformation,Lambertian object,albedo distribution,entropy minimization,generalized bas-relief ambiguity,intuitive reasoning,light source direction,light source strength,machine vision,surface geometry,uncalibrated photometric stereo
Computer vision,Finite set,Computer science,Computational geometry,Albedo,Minimisation (psychology),Probability distribution,Artificial intelligence,Prior probability,Ambiguity,Photometric stereo
Conference
Volume
Issue
ISSN
2007
1
1063-6919
Citations 
PageRank 
References 
47
1.40
11
Authors
3
Name
Order
Citations
PageRank
Neil G. Alldrin12708.45
Satya P. Mallick222810.70
David Kriegman37693451.96