Incorporating object-centered sampling and Delaunay tetrahedrization for visual hull reconstruction

Abstract

In this paper we present a novel shape from silhouette algorithm. For an object to be modeled, the algorithm first computes a cloud of points located on a pencil of rays and distributed evenly on the visual hull surface, inside and outside the visual hull. Then Delaunay tetrahedrization is applied to the point cloud to partition its convex hull into a set of tetrahedrons. Finally, outlier tetrahedrons are removed by tetrahedron peeling, and a mesh model of the visual hull is extracted. The algorithm is robust, free from discretization artifacts, and produces a mesh model composed of well-shaped triangles.