Abstract
This paper provides an overview of our joint work on graph-matching. We commence by reviewing the literature which has motivated this work. We then proceed to review our contributions under the headings of 1) the probabilistic framework, 2) search and optimisation, 3) matrix methods, 4) segmentation and grouping, 5) learning and 6) applications.
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Hancock, E., Wilson, R.C. (2002). Graph-Based Methods for Vision: A Yorkist Manifesto. In: Caelli, T., Amin, A., Duin, R.P.W., de Ridder, D., Kamel, M. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2002. Lecture Notes in Computer Science, vol 2396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70659-3_3
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DOI: https://doi.org/10.1007/3-540-70659-3_3
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