3D shape representation using Gaussian curvature co-occurrence matrix

4Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Co-occurrence matrix is traditionally used for the representation of texture information. In this paper, the co-occurrence matrix is combined with Gaussian curvature for 3D shape representation and a novel 3D shape description approach named Gaussian curvature co-occurrence matrix is proposed. Normalization process to Gaussian curvature co-occurrence matrix and the invariants independence of the translation, scaling and rotation transforms are demonstrated. Experiments indicate a better classification rate and running complexity to objects with slight different shape characteristic compared with traditional methods. © 2010 Springer-Verlag.

Cite

CITATION STYLE

APA

Guo, K. (2010). 3D shape representation using Gaussian curvature co-occurrence matrix. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6319 LNAI, pp. 373–380). https://doi.org/10.1007/978-3-642-16530-6_44

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free