Building 3D models of real-world objects by assembling views taken by a range sensor promises to be a more efficient method than manually producing CAD drawings. In this technique, a series of range images are acquired and then registered or aligned with each other to a high degree of accuracy. Finally, the polygonal meshes corresponding to the range images are merged to form a complete 3D model consisting of a single mesh. Many techniques have been proposed to solve the registration problem; however, little work has been done to date to compare several registration algorithms with the same sets of data. In this paper, we examine a software test-bed built for performing such comparisons. Within this test-bed, we have implemented several common registration algorithm variants to the baseline Iterative Closest Point (ICP) algorithm and tested them on partially overlapping range images taken from four different objects.
Gerald Dalley, Patrick J. Flynn