Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6787
Title: Graph-based shape indexing
Authors: Demirci, Muhammed Fatih
Keywords: Shape indexing
Laplacian spectrum
Majorization
Matrix analysis
Information retrieval
Issue Date: 2012
Publisher: Springer
Abstract: Graphs have become growingly important in representing shapes in computer vision. Given a query graph, it is essential to retrieve similar database graphs efficiently from a large database. In this paper, we present a graph-based indexing technique which overcomes significant drawbacks of the previous work (Demirci et al. in Comput Vis Image Underst 110(3):312-325, 2008) using a recently developed theorem from the domain of matrix analysis. Our technique starts by representing the topological structure of a graph in a vector space. As done in the previous work, the topological structure of a graph is constructed using its Laplacian spectra. However, unlike the previous approach, which represents all sugraphs of a database graph in the vector space to account for local similarity, a database graph in the proposed framework is represented as a single vector. By performing a range search around the query, the proposed indexing technique returns a set with both partial and global similarity. Empirical evaluation of the algorithm on an extensive set of retrieval trials including a comparison with the previous approach in both 2D and 3D demonstrates the effectiveness, efficiency, and robustness of the overall approach.
URI: https://doi.org/10.1007/s00138-010-0290-z
https://hdl.handle.net/20.500.11851/6787
ISSN: 0932-8092
1432-1769
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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