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2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Edge-preserving photometric stereo via depth fusion
Providence, RI USA
June 16-June 21
ISBN: 978-1-4673-1226-4
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 ill-conditioned 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 state-of-the-art in sensor fusion.
Index Terms:
stereo image processing,edge detection,image fusion,iterative methods,optimisation,nonlinear cost function,edge-preserving photometric stereo,depth fusion,sensor fusion scheme,active stereo,iterative optimization scheme,shadow area detection,image-based heuristics,ill-conditioned pixels,Optimization,Light sources,Stereo vision,Lighting,Sensor fusion,Image reconstruction,Cameras
Citation:
Huimin Yu, B. Wilburn, Ruigang Yang, Y. Matsushita, Mao Ye, Qing Zhang, "Edge-preserving photometric stereo via depth fusion," cvpr, pp.2472-2479, 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012
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