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Video indexing and similarity retrieval by largest common subgraph detection using decision trees

Shearer, Kim, Bunke, Horst and Venkatesh, Svetha 2001, Video indexing and similarity retrieval by largest common subgraph detection using decision trees, Pattern recognition, vol. 34, no. 5, pp. 1075-1091, doi: 10.1016/S0031-3203(00)00048-0.

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Title Video indexing and similarity retrieval by largest common subgraph detection using decision trees
Author(s) Shearer, Kim
Bunke, Horst
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Journal name Pattern recognition
Volume number 34
Issue number 5
Start page 1075
End page 1091
Total pages 17
Publisher Pergamon
Place of publication London, England
Publication date 2001-05
ISSN 0031-3203
1873-5142
Keyword(s) decision tree
graph matching
similarity retrieval
video indexing
Summary While the largest common subgraph (LCSG) between a query and a database of models can provide an elegant and intuitive measure of similarity for many applications, it is computationally expensive to compute. Recently developed algorithms for subgraph isomorphism detection take advantage of prior knowledge of a database of models to improve the speed of on-line matching. This paper presents a new algorithm based on similar principles to solve the largest common subgraph problem. The new algorithm significantly reduces the computational complexity of detection of the LCSG between a known database of models, and a query given on-line.
Language eng
DOI 10.1016/S0031-3203(00)00048-0
Field of Research 080305 Multimedia Programming
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2001, Pattern Recognition Society
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044293

Document type: Journal Article
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.