Title :
Segmentation of 3D Meshes Usingp-Spectral Clustering
Author :
Chahhou, Mohamed ; Moumoun, Lahcen ; El Far, Mohamed ; Gadi, Taoufiq
Author_Institution :
Fac. of Sci. Dhar Mahraz, Univ. Sidi Mohamed Ben Abdellah, Fes, Morocco
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.
Keywords :
computer graphics; matrix algebra; mesh generation; pattern clustering; 3D mesh segmentation; adjacency matrix; optimal Cheeger cut value; optimal segmentation; p-spectral clustering; rule clustering; spectral clustering; Benchmark testing; Clustering algorithms; Eigenvalues and eigenfunctions; Laplace equations; Silicon; Standards; Three-dimensional displays; 3D mesh; Cheeger cuts; minima rule; segmentation; spectral clustering;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2013.2297314
