%Aigaion2 BibTeX export from Idiap Publications
%Thursday 21 November 2024 10:07:51 AM

@ARTICLE{SBV00,
         author = {Shearer, Kim and Bunke, Horst and Venkatesh, Svetha},
       projects = {Idiap},
          title = {Video Indexing and Similarity Retrieval by Largest Common Subgraph Detection using Decision Trees},
        journal = {Pattern Recognition},
         volume = {34},
         number = {05},
           year = {2000},
       crossref = {sbv00tr},
       abstract = {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 online 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 know database of models, and a query given online.},
            pdf = {https://publications.idiap.ch/attachments/reports/2000/rr00-15.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2000/rr00-15.ps.gz},
ipdmembership={vision},
}



crossreferenced publications: 
@TECHREPORT{SBV00TR,
         author = {Shearer, Kim and Bunke, Horst and Venkatesh, Svetha},
       projects = {Idiap},
          title = {Video Indexing and Similarity Retrieval by Largest Common Subgraph Detection using Decision Trees},
           type = {Idiap-RR},
         number = {Idiap-RR-15-2000},
           year = {2000},
    institution = {IDIAP},
       abstract = {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 online 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 know database of models, and a query given online.},
            pdf = {https://publications.idiap.ch/attachments/reports/2000/rr00-15.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2000/rr00-15.ps.gz},
ipdmembership={vision},
}