Levenshtein distance for graph spectral features

  title={Levenshtein distance for graph spectral features},
  author={Richard C. Wilson and Edwin R. Hancock},
  journal={Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.},
  pages={489-492 Vol.2}
Graph structures play a critical role in computer vision, but they are inconvenient to use in pattern recognition tasks because of their combinatorial nature and the consequent difficulty in constructing feature vectors. Spectral representations have been used for this task which are based on the eigensystem of the graph Laplacian matrix. However, graphs of different sizes produce eigensystems of different sizes where not all eigenmodes are present in both graphs. We use the Levenshtein… CONTINUE READING
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