By Topic

Segmentation of 3D Meshes Usingp-Spectral Clustering

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Mohamed Chahhou ; Fac. of Sci. Dhar Mahraz, Univ. Sidi Mohamed Ben Abdellah, Fes, Morocco ; Lahcen Moumoun ; Mohamed El Far ; Taoufiq Gadi

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.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:36 ,  Issue: 8 )