Matching technology of point cloud model based on statistical features

To make matching result converge to global optimal solution,a point cloud model matching technology based on statistical features was proposed.The model matching was realized through keeping corresponding statistical features of free model and fixed model consistent.The statistical-features-based matching was classified as:complete matching and segment matching.Complete matching could be matched without the second try,but the segment matching needed follow-up handling to finish model matching:interactively adjust unconstrained degrees of freedom to acquire the visually matching of free model and fixed model,and then accurately match them by using Iterative Closest Point(ICP)algorithm.The matching scheme which used statistical features was stable and reliable,and it also guaranteed that the matching result was converged to global optimal solution.