By Topic

Color Constrained ICP for Registration of Large Unstructured 3D Color Data Sets

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

3 Author(s)
S. Druon ; University of Montpellier2-CNRS, Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier, 161 rue Ada, 34392 MONTPELLIER - FRANCE ; M. J. Aldon ; A. Crosnier

In this paper, we address the problem of pair-wise registration of large unstructured 3D/color datasets. Our purpose is to improve the classical ICP (Iterative closest point) algorithm by using color information, in order to deal with large datasets and with objects for which the geometric information is not significant enough. After a brief presentation of classical ICP (iterative closest point) algorithm and of the research works developed to improve its performance, we propose a new strategy to improve the selection of points. Color information is used to reduce the search space during the matching step. Experimental results obtained with real range images show that the algorithm provides an accurate estimation of the rigid transformation

Published in:

2006 IEEE International Conference on Information Acquisition

Date of Conference:

20-23 Aug. 2006