Edge-preserving photometric stereo via depth fusion

We present a sensor fusion scheme that combines active stereo with photometric stereo. Aiming at capturing full-frame depth for dynamic scenes at a minimum of three lighting conditions, we formulate an iterative optimization scheme that (1) adaptively adjusts the contribution from photometric stereo so that discontinuity can be preserved; (2) detects shadow areas by checking the visibility of the estimated point with respect to the light source, instead of using image-based heuristics; and (3) behaves well for illconditioned pixels that are under shadow, which are inevitable in almost any scene. Furthermore, we decompose our non-linear cost function into subproblems that can be optimized efficiently using linear techniques. Experiments show significantly improved results over the previous stateof-the-art in sensor fusion.

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Qing Zhang, Mao Ye, Ruigang Yang, Yasuyuki Matsushita, Bennett Wilburn, Huimin Yu
• Keywords: Computer Vision, Cvpr 2012, Iterative Optimization, Optimization Scheme, Sensor Fusion