Fast global registration of 3D sampled surfaces using a multi-z-buffer technique

We present a new method for the global registration of several overlapping 3D surfaces sampled on an object. The method is based on the ICP (iterative closest point) algorithm and on a segmentation of the sampled points in an optimized set of z-buffers. This multi-z-buffer technique provides a 3D space partitioning which greatly accelerates the search of the nearest neighbours in the establishment of the point-to-point correspondence between overlapping surfaces. Then a randomized iterative registration is processed on the surface set. We have tested an implementation of this technique on real sampled surfaces. It appears to be rapid accurate and robust, especially in the case of highly curved objects.