Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17038
Title: A neural network strategy for 3D surface registration
Authors: Liu, H
Yan, J
Zhang, D 
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2006, v. 3980 LNCS, p. 528-536 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: 3D surface registration is commonly used in shape analysis, surface representation, and medical image aided surgery. This technique is extremely computationally expensive and sometimes will lead to bad result configured with unstructured mass data for its' iterative searching procedure and ill-suited distance function. In this paper, we propose a novel neural network strategy for surface registration. Before that, a typical preprocessing procedure-mesh PCA is used for coordinate direction normalization. The results and comparisons show such neural network method is a promising approach for 3D shape matching.
Description: ICCSA 2006: International Conference on Computational Science and Its Applications, Glasgow, 8-11 May 2006
URI: http://hdl.handle.net/10397/17038
ISBN: 354034070X
9783540340706
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/11751540_56
Appears in Collections:Conference Paper

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