Simultaneous Registration of Multiple Range Views for Use in Reverse Engineering of CAD Models

摘要

When reverse engineering a CAD model, it is necessary to integrate information from several views of an object into a common reference frame. Given a rough initial alignment of local 3-D shape data in several images, further refinement is achieved using an improved version of the recently popular Iterative Closest Point algorithm. Improved data correspondence is determined by considering the merging data sets as a whole. A potentially incorrect distance threshold for removing outlier correspondences is not needed as in previous efforts. Incremental pose adjustments are computed simultaneously for all data sets, resulting in a more globally optimal set of transformations. Individual motion updates are computed using force-based optimization, by considering the data sets as implicitly connected by groups of springs. Experiments on both 2-D and 3-D data sets show that convergence is possible even for very rough initial positionings, and that the final registration accuracy typically approaches less than one quarter of the interpoint sampling resolution of the images.