Segmentation of discrete point clouds using an extensible set of templates

We present an algorithm for segmenting a discrete three-dimensional point-set (i.e., partitioning an input discrete point-set into appropriate subsets). The algorithm consists in the iteration of two main steps which are: fitting the parameters of template primitives from a user-specified list of primitives and extracting the points from the input point-set matching the best fitted primitive. We illustrate the results of applying our algorithm to several examples of three-dimensional point-sets.

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