An Eigendecomposition Approach to Weighted Graph Matching Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Laplace eigenvalues of graphs—a survey
Discrete Mathematics - Algebraic graph theory; a volume dedicated to Gert Sabidussi
On Median Graphs: Properties, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Candid Covariance-Free Incremental Principal Component Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Entropy and Distance of Random Graphs with Application to Structural Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A PCA approach for fast retrieval of structural patterns inattributed graphs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust principal component analysis by self-organizing rules based on statistical physics approach
IEEE Transactions on Neural Networks
Bounding the Size of the Median Graph
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Evaluation of Spectral-Based Methods for Median Graph Computation
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Median graphs: A genetic approach based on new theoretical properties
Pattern Recognition
A Recursive Embedding Approach to Median Graph Computation
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
A generic framework for median graph computation based on a recursive embedding approach
Computer Vision and Image Understanding
Spectral median graphs applied to graphical symbol recognition
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
On the relation between the common labelling and the median graph
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
A comparison between structural and embedding methods for graph classification
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
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In pattern recognition, median computation is an important technique for capturing the important information of a given set of patterns but it has the main drawback of its exponential complexity. Moreover, the Spectral Graph techniques can be used for the fast computation of the approximate graph matching error, with a considerably reduced execution complexity. In this paper, we merge both methods to define the Median Spectral Graphs. With the use of the Spectral Graph theories, we find good approximations of median graph. Experiments on randomly generated graphs demonstrate that this method works well and it is robust against noise.