We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
We describe a novel viewpoint-lighting ambiguity which we call the KGBR. This ambiguity assumes orthographic projection or an affine camera, and uses Lambertian reflectance functi...
We consider the problem of image comparison in order to match smooth surfaces under varying illumination. In a smooth surface nearby surface normals are highly correlated. We model...
Margarita Osadchy, Michael Lindenbaum, David W. Ja...
We consider the problem of estimating the 3D shape and reflectance properties of an object made of a single material from a calibrated set of multiple views. To model reflectance, ...
This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...