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Photometric stereo with uncalibrated lights determines surface orientations ambiguously up to any regular transformation. If the surface reflectance model is separable with respect to the illumination and viewing directions, its inherent symmetries enable to design two previously unrecognized constraints on normals that reduce this ambiguity. The two(More)
Matching of high-dimensional features using nearest neighbors search is an important part of image matching methods which are based on local invariant features. In this work we highlight effects pertinent to high-dimensional spaces that are significant for matching, yet have not been explicitly accounted for in previous work. In our approach, we require(More)
Helmholtz Stereopsis (HS) has recently been explored as a promising technique for capturing shape of objects with unknown reflectance. So far, it has been widely applied to objects of smooth geometry and piecewise uniform Bidi-rectional Reflectance Distribution Function (BRDF). Moreover , for non-convex surfaces the inter-reflection effects have been(More)
Helmholtz stereopsis guarantees unbiasedness by BRDF of the search for inter-image correspondences. In a practical setup, calibrated pixel sensitivity and corrected light anisotropy are required for the method to work well. In this paper a simple method for joint light-camera radiomet-ric calibration is proposed. Such calibration is shown to be an ill-posed(More)
A conceptually very simple unsupervised algorithm for learning structure in the form of a hierarchical probabilistic model is described in this paper. The proposed probabilistic model can easily work with any type of image primitives such as edge segments, non-max-suppressed filter set responses, texels, distinct image regions, SIFT features, etc., and is(More)