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Deterministic search strategies for relational graph matching

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Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1223))

Abstract

This paper describes a comparative study of various deterministic discrete search-strategies for graph-matching. The framework for our study is provided by the Bayesian consistency measure recently reported by Wilson and Hancock [47–49]. We investigate two classes of update process. The first of these aim to exploit discrete gradient ascent methods. We investigate the effect of searching in the direction of both the local and global gradient maximum. An experimental study demonstrates that although more computationally intensive, the global gradient method offers significant performance advantages in terms of accuracy of match. Our second search strategy is based on tabu search. In order to develop this method we introduce memory into the search procedure by defining context dependant search paths. We illustrate that although it is more efficient than the global gradient method, tabu search delivers almost comparable performance.

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Author information

Authors and Affiliations

  1. Defence Research Agency, St Andrews Road, WR14 3PS, Malvern, Worcestershire, UK

    Mark L. Williams

  2. Department of Computer Science, University of York, Y01 5DD, York, UK

    Richard C. Wilson & Edwin R. Hancock

Authors
  1. Mark L. Williams
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  2. Richard C. Wilson
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  3. Edwin R. Hancock
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Editor information

Marcello Pelillo Edwin R. Hancock

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© 1997 Springer-Verlag Berlin Heidelberg

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Williams, M.L., Wilson, R.C., Hancock, E.R. (1997). Deterministic search strategies for relational graph matching. In: Pelillo, M., Hancock, E.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 1997. Lecture Notes in Computer Science, vol 1223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62909-2_85

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  • DOI: https://doi.org/10.1007/3-540-62909-2_85

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62909-2

  • Online ISBN: 978-3-540-69042-9

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