Example-Based Photometric Stereo: Shape Reconstruction with General, Varying BRDFs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color Subspaces as Photometric Invariants
International Journal of Computer Vision
Towards full 3D Helmholtz stereovision algorithms
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Accurate real-time neural disparity MAP estimation with FPGA
Pattern Recognition
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Helmholtz stereopsis has been introduced recently as a surfacereconstruction technique that does not assume a modelof surface reflectance. In the reported formulation, correspondencewas established using a rank constraint, necessitatingat least three viewpoints and three pairs of images.Here, it is revealed that the fundamental Helmholtz stereopsisconstraint defines a nonlinear partial differential equation,which can be solved using only two images. It is shownthat, unlike conventional stereo, binocular Helmholtz stereopsisis able to establish correspondence (and thereby recoversurface depth) for objects having an arbitrary andunknown BRDF and in textureless regions (i.e., regions ofconstant or slowly varying BRDF). An implementation andexperimental results validate the method for specular surfaceswith and without texture.