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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.

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Title An efficient least common subgraph algorithm for video indexing
Author(s) Shearer, Kim
Venkatesh, Svetha
Bunke, Horst
Conference name International Conference on Pattern Recognition (14th : 1998 : Brisbane, Qld.)
Conference location Brisbane, Qld.
Conference dates 16-20 Aug. 1998
Title of proceedings ICPR 1998 : Proceedings of the 14th International Conference on Pattern Recognition
Editor(s) Jain, Anil K.
Venkatesh, Svetha
Lovell, Brian Carrington
Publication date 1998
Conference series International Conference on Pattern Recognition
Start page 1241
End page 1243
Total pages 3
Publisher IEEE
Place of publication Los Alamitos, Calif.
Keyword(s) graph matching algorithms
largest common subgraph
least common subgraph algorithm
online classification
similarity
video indexing
Summary 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.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 0818685131
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©1998, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044870

Document type: Conference Paper
Collections: School of Information Technology
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