Kernel on Graphs Based on Dictionary of Paths for Image Retrieval

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.