A Step Towards Unification of Syntactic and Statistical Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special memorial issue for Professor King-Sun Fu
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
An Eigendecomposition Approach to Weighted Graph Matching Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo Correspondence Through Feature Grouping and Maximal Cliques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Least-Squares Estimation of Transformation Parameters Between Two Point Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parameterized Point Pattern Matching and Its Application to Recognition of Object Families
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching by Discrete Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
Structural Graph Matching Using the EM Algorithm and Singular Value Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
A Linear Programming Approach for the Weighted Graph Matching Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A RKHS Interpolator-Based Graph Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Eigenspace Projection Clustering Method for Inexact Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Edit Distance from Spectral Seriation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hyper-graph matching via reweighted random walks
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Likelihood based hierarchical clustering
IEEE Transactions on Signal Processing
A graph-matching kernel for object categorization
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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The intrinsic information of a graph can be fully encoded into its spectrum and corresponding eigenvectors of its adjacency matrix, which provides a solid foundation for the success of spectral graph matching methods. The spectral multiplicity, however, may significantly affect the matching accuracy. In this paper, we propose a spectral-multiplicity-tolerant graph matching approach. We start from modeling the spectral multiplicity in the matching error measurement. Next, we address the equal-size graph matching problem, and show how to establish the vertex-to-vertex correspondence by alternatively optimizing the multiplicity matrix C and the permutation matrix P. We also propose a reliable initialization method to make the iterative optimization process converge rapidly. Then, we extend the algorithm to unequal-size graph matching by optimally warping two graphs into the same size. A comprehensive performance evaluation has been conducted on a large synthetic dataset. We also demonstrate the effectiveness of our approach on shape retrieval. The experimental results show that compared with existing methods, the proposed approach is more robust to noise and structural corruption and has a comparable complexity.