Abstract
This paper describes a novel approach to relational matching problems which draws on an active graph paradigm. This active representation is iteratively reconfigured to increase its degree of topological congruency with the model relational structure in a reconstructive matching process. The final restored graph representation is optimal in the sense that it has maximum a posteriori probability with respect to the available attributes for the objects under match. Reassignment of nodes between the graph and an outlier set iteratively optimises the Kullback entropy of the surviving relational cluster. The main benefit of the reconstructive technique over the conventional matching of static relational structures, lies in its rejection of relational noise and an increased robustness to severe levels of scene clutter.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
D. Ackley, G. Hinton and T. Sejnowski,“A Learning Algorithm for Boltzmann Machines”, Cognitive Science, 9, pp 147–165, 1985.
D. Geiger and F. Girosi, “Parallel and Deterministic Algorithms from MRF's: Surface Reconstruction”, IEEE PAMI, 13, pp 401–412, 1991.
E.R.Hancock and J.Kittler, “Discrete Relaxation,” Pattern Recognition,23, pp.711–733, 1990.
B.T. Messmer and H Bunke, “Efficient error-tolerant subgraph isomorphism detection”, Shape, Structure and Pattern Recognition, edited by D Dori and A Bruchstein, 1994.
K. Rose, E.Gurewitz and G.C. Fox, “Constrained Clustering as an Optimisation Method”, IEEE PAMI, 15, pp 785–794, 1993.
P.J. Rousseeuw, “Robust Regression and Outlier Detection”, Wiley, New York, 1987.
Sanfeliu A. and Fu K.S., “A Distance Measure Between Attributed Relational Graphs for Pattern Recognition”, IEEE SMC, 13, pp 353–362, 1983.
L Shapiro and R.M.Haralick, “A Metric for Comparing Relational Descriptions”, IEEE PAMI, 7, pp 90–94, 1985.
R.C. Wilson and E.R Hancock, “Graph Matching by Discrete Relaxation”, Pattern Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems, North Holland pp. 165–177, 1994.
Wong A.K.C. and You M., “Entropy and Distance of Random Graphs with Application to Structural Pattern Recognition”, IEEE PAMI, 7, pp 599–609, 1985.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1995 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wilson, R.C., Hancock, E.R. (1995). Relational matching with active graphs. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_314
Download citation
DOI: https://doi.org/10.1007/3-540-60268-2_314
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-60268-2
Online ISBN: 978-3-540-44781-8
eBook Packages: Springer Book Archive