Shape from shading using graph cuts
Pattern Recognition
Canonical subsets of image features
Computer Vision and Image Understanding
Semidefinite Programming Heuristics for Surface Reconstruction Ambiguities
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
User-guided shape from shading to reconstruct fine details from a single photograph
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Shape and Refractive Index from Single-View Spectro-Polarimetric Images
International Journal of Computer Vision
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Resolving local ambiguities is an important issue for shape from shading (SFS). Pixel ambiguities of SFS can be eliminated by propagation approaches. However, patch ambiguities still exist. Therefore, we formulate the global disambiguation problem to resolve these ambiguities. Intuitively, it can be interpreted as flipping patches and adjusting heights such that the result surface has no kinks. The problemis intractable because exponentially many possible configurations need to be checked. Alternatively, we solve the integrability testing problems closely related to the original one. It can be viewed as finding a surface which satisfies the global integrability constraint. To encode the constraints, we introduce a graph formulation called configuration graph. Searching the solution on this graph can be reduced to a Max-cut problem and its solution is computuble using semidefinite programming (SDP) relaxation. Tests carried out on synthetic and real images show that the global disambiguation works well for complex shapes.