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Segmentation of 3D Meshes Using p-Spectral Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
|September 10, 2015
Abstract:
In this paper, we propose a new approach to get the optimal segmentation of a 3D mesh as a human can perceive using the minima rule and spectral clustering. This method is fully unsupervised and provides a hierarchical segmentation via recursive cuts. We introduce a new concept of the adjacency matrix based on cognitive studies. We also introduce the use of one-spectral clustering which leads to the optimal Cheeger cut value.

