Reconstruction of specular surfaces via probabilistic voxel carving

摘要

Reconstruction of specular objects from camera images is a notoriously difficult task. We propose a novel approach to recover specular surfaces based on probabilistic voxel carving model. The energy functional formulation of the problem might eventually enable the fusion of all sorts of available information, such as the a priori shape hypotheses, knowledge of motion parameters or the reflected environment etc. The model and the specular energy components are discussed in detail. As the first application, we demonstrate the fusion of multiple regularization-free deflectometric datasets recorded from different camera positions.