Abstract
Algorithms that perform segmentation and surface approximation of range images need to be robust since real range data tends to be noisy. In this paper, we present a robust clustering algorithm and show how it can be used to obtain an approximation of a range image in terms of quadric surface patches. The proposed algorithm does not assume that the number of surface patches is known a priori, and performs well even when the data set is contaminated by noise and outliers.
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