An octree-based method for shape from inconsistent silhouettes
Shape-from-Silhouette (SfS) is the widely known problem of obtaining the 3D structure of an object from its silhouettes. Two main approaches can be employed: those based on voxel sets, which perform an exhaustive search of the working space, and those based on octrees, which perform a top-down analysis that speeds up the computation. The main problem of both approaches is the need for perfect silhouettes to obtain accurate results. Perfect background subtraction hardly ever happens in realistic scenarios, so these techniques are restricted to controlled environments where the consistency hypothesis can be assumed. Recently, some approaches (all of them based on voxel sets) have been proposed to solve the problem of inconsistency. Their main drawback is the high computational cost required to perform an exhaustive analysis of the working space. This paper proposes a novel approach to solve SfS with inconsistent silhouettes from an octree based perspective. The inconsistencies are dealt by means of the DempsterShafer (DS) theory and we employ a Butterworth function for adapting threshold values in each resolution level of the octree. The results obtained show that our proposal provides higher reconstruction quality than the standard octree based methods in realistic environments. When compared to voxel set approaches that manage inconsistency, our method obtains similar results with a reduction in the computing time of an order of magnitude.
octrees shape from silhouette evidence theory