Structural Indexing: Efficient 3-D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Building 3-D models from unregistered range images
Graphical Models and Image Processing
Partial Surface and Volume Matching in Three Dimensions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Point Signatures: A New Representation for 3D Object Recognition
International Journal of Computer Vision
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Surface registration by matching oriented points
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Free-Form Surface Registration Using Surface Signatures
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Matching 3D Models with Shape Distributions
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Harmonic shape images: a three-dimensional free-form surface representation and its applications in surface matching
Multiview registration for large data sets
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Geometry and Convergence Analysis of Algorithms for Registration of 3D Shapes
International Journal of Computer Vision
Generalized surface flows for mesh processing
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
3D registration by using an alternative 3D shape representation
ISCGAV'07 Proceedings of the 7th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
Invariant features for automatic coarse registration of point-based surfaces
ISCGAV'06 Proceedings of the 6th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
A coarse-to-fine algorithm for 3D registration based on wavelet decomposition
WSEAS TRANSACTIONS on SYSTEMS
Feature level fusion of range and intensity images of an object
International Journal of Computational Vision and Robotics
A coarse-to-fine algorithm for 3D registration based on wavelet decomposition
ICS'08 Proceedings of the 12th WSEAS international conference on Systems
Affine iterative closest point algorithm for point set registration
Pattern Recognition Letters
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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.