The correspondence framework for 3D surface matching algorithms

Planitz, B. M., Maeder, A. J. and Williams, J. A. (2005) The correspondence framework for 3D surface matching algorithms. Computer Vision and Image Understanding, 97 3: 347-383. doi:10.1016/j.cviu.2004.08.001

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Author Planitz, B. M.
Maeder, A. J.
Williams, J. A.
Title The correspondence framework for 3D surface matching algorithms
Journal name Computer Vision and Image Understanding   Check publisher's open access policy
ISSN 1007-3142
Publication date 2005
Sub-type Article (original research)
DOI 10.1016/j.cviu.2004.08.001
Volume 97
Issue 3
Start page 347
End page 383
Total pages 37
Editor A. Kak
Place of publication The Netherlands
Publisher Elsevier
Collection year 2005
Language eng
Subject C1
280208 Computer Vision
671304 Data, image and text equipment
Abstract Beyond the inherent technical challenges, current research into the three dimensional surface correspondence problem is hampered by a lack of uniform terminology, an abundance of application specific algorithms, and the absence of a consistent model for comparing existing approaches and developing new ones. This paper addresses these challenges by presenting a framework for analysing, comparing, developing, and implementing surface correspondence algorithms. The framework uses five distinct stages to establish correspondence between surfaces. It is general, encompassing a wide variety of existing techniques, and flexible, facilitating the synthesis of new correspondence algorithms. This paper presents a review of existing surface correspondence algorithms, and shows how they fit into the correspondence framework. It also shows how the framework can be used to analyse and compare existing algorithms and develop new algorithms using the framework's modular structure. Six algorithms, four existing and two new, are implemented using the framework. Each implemented algorithm is used to match a number of surface pairs. Results demonstrate that the correspondence framework implementations are faithful implementations of existing algorithms, and that powerful new surface correspondence algorithms can be created. (C) 2004 Elsevier Inc. All rights reserved.
Keyword Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Surface Matching
Object Recognition
Range Images
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

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Created: Wed, 15 Aug 2007, 06:35:45 EST