Although the Iterative Closest Point (ICP) algorithm has been an extremely popular method for 3D points or surface registration, it can only be applied to two point sets at a time. By only registering two scans at a time, ICP fails to exploit the redundant information available in multiple scans that have overlapping regions. In this paper, we present a multi-view extension of the ICP algorithm by a method that simultaneously averages the redundant information available in the scans with overlapping regions. Variants of this method that carry out such simultaneous registration in a causal manner and that utilise the transitive property of point correspondences are also presented. The improved accuracy of this motion averaged approach in comparison with ICP and some multi-view methods is established through multiple tests. We also present results of our method applied to some well-known real datasets.
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Pooja et al. (2010) studied this question.
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