A semisupervised approach to space carving

In this paper, we present a semi supervised approach to space carving. We do this by casting the recovery of volumetric data from multiple views into an evidence combining setting. The method presented here is statistical in nature and employs, as a starting point, a manually obtained contour. By making use of this user-provided information, we learn a prior distribution that is then used to compute the probability of a voxel being carved. This evidence combining setting allows us to make use of background pixel information. As a result, our method combines the advantages of shape-from-silhouette techniques and statistical space carving approaches. We provide quantitative results and illustrate the utility of the method on real-world imagery.