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A clustering method based on quadric surface for segmentation of range data

In this paper, a clustering method is proposed to segment a range image of closed object. The data points are classified into domains with similar quadric surface. This method consists of two stages. First, new clusters are created on demand. Next, dispensable clusters are vanished by the competition of clusters, and remaining clusters are agglomerated. Consequently, optimal clusters are determined.