Dense Photometric Stereo Using a Mirror Sphere and Graph Cut

We present a surprisingly simple system that allows for robust normal reconstruction by dense photometric stereo, in the presence of severe shadows, highlight, transparencies, complex geometry, variable light intensity attenuation and inaccurate light directions. Our system consists of a mirror sphere, a spotlight and a DV camera only. Using this, we produce a dense set of unbiased but noisy photometric data uniformly distributed on the light direction sphere. We use this dense set to derive a very robust matching cost for our MRF photometric stereo model, where the Maximum A Posteriori (MAP) solution is estimated. To aggregate support for candidate normals in the normal refinement process, we introduce a compatibility function that is translated into a discontinuity-preserving metric, thus speeding up the MAP estimation by energy minimization using graph cut. No reference object of similar material is used. We perform detailed comparison on our approach with conventional convex minim...

• Type: Conference
• Year: 2005
• Where: CVPR
• Authors: Tai-Pang Wu, Chi-Keung Tang
• Keywords: Computer Vision, CVPR 2005, Dense Photometric Stereo, Dense Set, Light Direction Sphere, Mrf Photometric Stereo, Noisy Photometric Data