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
Closed-Form Solutions for Physically Based Shape Modeling and Recognition
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
Solution of the simultaneous pose and correspondence problem using Gaussian error model
Computer Vision and Image Understanding
Corner detection via topographic analysis of vector-potential
Pattern Recognition Letters
Structural Graph Matching Using the EM Algorithm and Singular Value Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
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
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
SoftPOSIT: Simultaneous Pose and Correspondence Determination
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
The Softassign Procrustes Matching Algorithm
IPMI '97 Proceedings of the 15th International Conference on Information Processing in Medical Imaging
Shape matching and registration by data-driven EM
Computer Vision and Image Understanding
Shape Learning with Function-Described Graphs
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
On affine registration of planar point sets using complex numbers
Computer Vision and Image Understanding
A Novel Kernel Correlation Model with the Correspondence Estimation
Journal of Mathematical Imaging and Vision
Smooth simultaneous structural graph matching and point-set registration
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
A new graph matching method for point-set correspondence using the EM algorithm and Softassign
Computer Vision and Image Understanding
A novel approach for affine point pattern matching
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
The alignment between 3-d data and articulated shapes with bending surfaces
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Graph matching based on spectral embedding with missing value
Pattern Recognition
Smooth point-set registration using neighboring constraints
Pattern Recognition Letters
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This paper casts the problem of 2D point-set alignment and correspondence matching into a unified framework. Our aim in providing this unification is to constrain the recovery of pose parameters using relational constraints provided by the structural arrangement of the points. This structural information is provided by a neighbourhood graph for the points. We characterise the problem using distinct probability distributions for alignment errors and correspondence errors. The utility measure underpinning the work is the cross-entropy between probability distributions for alignment and assignment errors. This statistical framework interleaves the processes of finding point correspondences and estimating the alignment parameters. In the case of correspondence matching, the probability distribution models departures from edge consistency in the matching of the neighbourhood graphs. We investigate two different models for the alignment error process. In the first of these, we study Procrustes alignment. Here we show how the parameters of the similarity transform and the correspondence matches can be located using dual singular value decompositions. The second alignment process uses a point-distribution model. We show how this augmented point-distribution model can be matched to unlabelled point-sets which are subject to both additional clutter and point drop-out. Experimental results using both synthetic and real images are given.