Efficient image signatures and similarities using tensor products of local descriptors
Computer Vision and Image Understanding
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Recent approaches of graph comparison consider graphs as sets of paths. Kernels on graphs are then computed from kernels on paths. A common strategy for graph retrieval is to perform pairwise comparisons. In this paper, we propose to follow a different strategy, where we collect a set of paths into a dictionary, and then project each graph to this dictionary. Then, graphs can be classified using powerful classification methods, such as SVM. Furthermore, we collect the paths through interaction with a user. This strategy is ten times faster than a straight comparisons of paths. Experiments have been carried out on a database of city windows.