Registering 3D objects triangular meshes using an interest point detection on barycentric coordinates

Tibyani Tibyani, Sei Ichiro Kamata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper,we put forward an interest point detection framework and combine with a spin image algorithm to register them. A framework is presented in this study. This method make use of the Harris Operator Extension method of interest point detection on 3D manifold triangular meshes in barycentric coordinate. Using this approach, we can extract the object correctly and effectively in noise situation. The unique advantage of this framework is its applicability to triangular meshes models. Experimental results on a different number of models are shown to demonstrate more accurate and effectively results for global registering 3D Objects triangular meshes for three pairs of corresponding interest point features.

Original languageEnglish
Title of host publication2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012
Pages122-127
Number of pages6
DOIs
Publication statusPublished - 2012 Nov 26
Event2012 1st International Conference on Informatics, Electronics and Vision, ICIEV 2012 - Dhaka, Bangladesh
Duration: 2012 May 182012 May 19

Publication series

Name2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012

Conference

Conference2012 1st International Conference on Informatics, Electronics and Vision, ICIEV 2012
CountryBangladesh
CityDhaka
Period12/5/1812/5/19

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Information Systems
  • Electrical and Electronic Engineering

Cite this

Tibyani, T., & Kamata, S. I. (2012). Registering 3D objects triangular meshes using an interest point detection on barycentric coordinates. In 2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012 (pp. 122-127). [6317548] (2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012). https://doi.org/10.1109/ICIEV.2012.6317548