Towards live monocular 3d laparoscopy using shading and specularity information
IPCAI'12 Proceedings of the Third international conference on Information Processing in Computer-Assisted Interventions
Shapecollage: occlusion-aware, example-based shape interpretation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Color constancy, intrinsic images, and shape estimation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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We relax the long-held and problematic assumption in shape-from-shading (SFS) that albedo must be uniform or known, and address the problem of "shape and albedo from shading" (SAFS). Using models normally reserved for natural image statistics, we impose "naturalness" priors over the albedo and shape of a scene, which allows us to simultaneously recover the most likely albedo and shape that explain a single image. A simplification of our algorithm solves classic SFS, and our SAFS algorithm can solve the intrinsic image decomposition problem, as it solves a superset of that problem. We present results for SAFS, SFS, and intrinsic image decomposition on real lunar imagery from the Apollo missions, on our own pseudo-synthetic lunar dataset, and on a subset of the MIT Intrinsic Images dataset[15]. Our one unified technique appears to outperform the previous best individual algorithms for all three tasks. Our technique allows a coarse observation of shape (from a laser rangefinder or a stereo algorithm, etc) to be incorporated a priori. We demonstrate that even a small amount of low-frequency information dramatically improves performance, and motivate the usage of shading for high-frequency shape (and albedo) recovery.