This paper provides an overview of our joint work on graphmatching. 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.
CITATION STYLE
Hancock, E., & Wilson, R. C. (2002). Graph-based methods for vision: A yorkist manifesto. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2396, pp. 31–46). Springer Verlag. https://doi.org/10.1007/3-540-70659-3_3
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