An Eigendecomposition Approach to Weighted Graph Matching Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representing stereo data with the Delaunay triangulation
Artificial Intelligence
Least-Squares Estimation of Transformation Parameters Between Two Point Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-based correspondence: an eigenvector approach
Image and Vision Computing - Special issue: BMVC 1991
Parameterized Point Pattern Matching and Its Application to Recognition of Object Families
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Active shape models—their training and application
Computer Vision and Image Understanding
Graphical Templates for Model Registration
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Graph Matching With a Dual-Step EM Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Corner detection via topographic analysis of vector-potential
Pattern Recognition Letters
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Modal Matching for Correspondence and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Similarity and Affine Invariant Distances Between 2D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Lagrangian relaxation network for graph matching
IEEE Transactions on Neural Networks
Memorizing Visual Knowledge for Assembly Process Monitoring
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
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This paper casts the problem of point-set alignment and correspondence into a united framework. The utility measure underpinning the work is the cross-entropy between probability distributions for alignment and assignment errors. We show how Procrustes alignment parameters and correspondence probabilities can be located using dual singular value decompositions. Experimental results using both synthetic and real images are given.