3DOR 08
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Browsing 3DOR 08 by Subject "Categories and Subject Descriptors (according to ACM CCS): H.3.3 [Information Search and Retrieval]: Retrieval Models I.5.1 [Models]: Statistical"
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Item Similarity Score Fusion by Ranking Risk Minimization for 3D Object Retrieval(The Eurographics Association, 2008) Akgül, Ceyhun Burak; Sankur, Bülent; Yemez, Yücel; Schmitt, Francis; Stavros Perantonis and Nikolaos Sapidis and Michela Spagnuolo and Daniel ThalmannIn this work, we introduce a score fusion scheme to improve the 3D object retrieval performance. The state of the art in 3D object retrieval shows that no single descriptor is capable of providing fine grain discrimination required by prospective 3D search engines. The proposed fusion algorithm linearly combines similarity information originating from multiple shape descriptors and learns their optimal combination of weights by minimizing the empirical ranking risk criterion. The algorithm is based on the statistical ranking framework [CLV07], for which consistency and fast rate of convergence of empirical ranking risk minimizers have been established. We report the results of ontology-driven and relevance feedback searches on a large 3D object database, the Princeton Shape Benchmark. Experiments show that, under query formulations with user intervention, the proposed score fusion scheme boosts the performance of the 3D retrieval machine significantly.