Fast Random Sample Matching of 3d Fragments

This paper proposes an efficient pairwise surface matching approach for the automatic assembly of 3d fragments or industrial components. The method rapidly scans through the space of all possible solutions by a special kind of random sample consensus (RANSAC) scheme. By using surface normals and optionally simple features like surface curvatures, we can highly constrain the initial 6 degrees of freedom search space of all relative transformations between two fragments. The suggested approach is robust, very time and memory efficient, easy to implement and applicable to all kinds of surface data where surface normals are available (e.g. range images, polygonal object representations, point clouds with neighbor connectivity, etc.).