An Eigendecomposition Approach to Weighted Graph Matching Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-based correspondence: an eigenvector approach
Image and Vision Computing - Special issue: BMVC 1991
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Active shape models—their training and application
Computer Vision and Image Understanding
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching by Discrete Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Image Corner Detection Through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Matching With a Dual-Step EM Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural matching with active triangulations
Computer Vision and Image Understanding
Corner detection via topographic analysis of vector-potential
Pattern Recognition Letters
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Graph Matching Using the EM Algorithm and Singular Value Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Modal Matching for Correspondence and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A direct method for stereo correspondence based on singular value decomposition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Feature Registration Framework Using Mixture Models
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Object Recognition as Many-to-Many Feature Matching
International Journal of Computer Vision
A Laplacian spectral method for stereo correspondence
Pattern Recognition Letters
Spectral Correspondence Using the TPS Deformation Model
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
A generative model for graph matching and embedding
Computer Vision and Image Understanding
Inexact Matching of Large and Sparse Graphs Using Laplacian Eigenvectors
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Interest points of general imbalance
IEEE Transactions on Image Processing
Manifold embedding for shape analysis
Neurocomputing
Probabilistic matching of lines for their homography
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Classifying transformation-variant attributed point patterns
Pattern Recognition
Versatile spectral methods for point set matching
Pattern Recognition Letters
Iterative 3D point-set registration based on hierarchical vertex signature (HVS)
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Comparative study of algorithms for matching sets of reference points
Pattern Recognition and Image Analysis
Fundamental matrix estimation by multiobjective genetic algorithm with Taguchi's method
Applied Soft Computing
Texture image retrieval: a feature-based correspondence method in fourier spectrum
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Chi-square goodness-of-fit test of 3d point correspondence for model similarity measure and analysis
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Kernel spectral correspondence matching using label consistency constraints
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Pattern analysis with graphs: Parallel work at Bern and York
Pattern Recognition Letters
Robust point pattern matching based on spectral context
Pattern Recognition
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Abstract--The modal correspondence method of Shapiro and Brady aims to match point-sets by comparing the eigenvectors of a pairwise point proximity matrix. Although elegant by means of its matrix representation, the method is notoriously susceptible to differences in the relational structure of the point-sets under consideration. In this paper, we demonstrate how the method can be rendered robust to structural differences by adopting a hierarchical approach. To do this, we place the modal matching problem in a probabilistic setting in which the correspondences between pairwise clusters can be used to constrain the individual point correspondences. We demonstrate the utility of the method on a number of synthetic and real-world point-pattern matching problems.