An efficient least common subgraph algorithm for video indexing
Shearer, Kim, Venkatesh, Svetha and Bunke, Horst 1998, An efficient least common subgraph algorithm for video indexing, in ICPR 1998 : Proceedings of the 14th International Conference on Pattern Recognition, IEEE, Los Alamitos, Calif., pp. 1241-1243.
Many tasks in computer vision can be expressed as graph problems. This allows the task to be solved using a well studied algorithm, however many of these algorithms are of exponential complexity. This is a disadvantage when considered in the context of searching a database of images or videos for similarity. Work by Mesaner and Bunke (1995) has suggested a new class of graph matching algorithms which uses a priori knowledge about a database of models to reduce the time taken during online classification. This paper presents a new algorithm which extends the earlier work to detection of the largest common subgraph.
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Field of Research
089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective
970108 Expanding Knowledge in the Information and Computing Sciences
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