Abstract:
Variants of the ICP algorithm are widely used in many vision- based applications, such as visual odometry, structure from motion, 3D reconstruction, or object segmentation. Establishing correct correspon- dences between two sets of 3D points, generated by stereo vision, needs to take those uncertainties into account. We propose a novel variant of the traditional ICP algorithm for solving the mentioned alignment problem. Our method, named incremental structured iterative closest point, aims at improved registrations of 3D points calculated for real world data. Evaluations are carried out by measuring the distances between two in- puts, in both local and global perspectives, and experimental results are visually presented in this paper.