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Surface approximation and range image segmentation through robust competitive clustering

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2 Author(s)
Frigui, H. ; Dept. of Comput. Eng. & Comput. Sci., Missouri Univ., Columbia, MO, USA ; Krishnapuram, R.

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

Published in:

Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on  (Volume:2 )

Date of Conference:

8-11 Sep 1996