Fast approximation of range images by triangular meshes generated through adaptive randomized sampling
Miguel Ángel García · 2002
This paper describes and evaluates an efficient technique that allows the fast generation of 3D triangular meshes from range images avoiding optimization procedures. Such a tool is advantageous in order to integrate range imagery into world models based on scattered representations. Furthermore, this technique can also be used as a fast preprocessing stage of registration, segmentation or recognition algorithms, owing to its abstraction capabilities that tend to eliminate redundant information. The proposed method has two stages: 1) the vertices of the mesh are computed through adaptive randomized sampling of the range image based on curvature estimations; and 2) the mesh is generated by triangulating the sampled vertices through an efficient 2 1/2 D Delaunay algorithm. The sampling process concentrates points in areas of large curvature and tends to preserve surface and orientation discontinuities. Multiresolution representations are supported in a natural way. The proposed technique is evaluated with several real range images that include both free-form and polyhedral surfaces.