Modeling Range Images with Bounded Error Triangular Meshes without Optimization

This paper presents a new technique for approximating range images by means of adaptive triangular meshes with a bounded approximation error and without applying optimization. This new approach consists of three stages. In the first stage, every pixel of the given range image is mapped to a 3D point defined in a reference frame associated with the range sensor. Then, those 3D points are mapped to a 3D curvature space. In the second stage, the points contained in this curvature space are triangulated through a 3D Delaunay algorithm, giving rise to a tetrahedronization of them. In the last stage, an iterative process starts digging the external surface of the previous tetrahedronization, removing those triangles that do not fulfill the given approximation error. In thi