3D-Model search engine from photos | Zendy

Tarik Filali Ansary | Zendy; Jean-Phillipe Vandeborre | Zendy; Mohamed Daoudi | Zendy

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3D-Model search engine from photos

Author(s) -

Tarik Filali Ansary,

Jean-Phillipe Vandeborre,

Mohamed Daoudi

Publication year - 2007

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/1282280.1282293

Subject(s) - search engine , computer science , benchmark (surveying) , information retrieval , spamdexing , 3d model , database search engine , metasearch engine , search oriented architecture , probabilistic logic , search analytics , statistical model , interface (matter) , data mining , machine learning , artificial intelligence , web search query , operating system , geodesy , geography , bubble , maximum bubble pressure method

In this paper, we present the FOX-MIIRE 3D-Model Search Engine. Our search engine is based on Adaptive Views Vlustering (AVC) algorithm [4]. The AVC method uses statistical model distribution scores to select the optimal number of views to characterise a 3D-model. The search engine also uses a probabilistic Bayesian method to retrieve 3D-models visualy similar to a query 3D-model, photos or sketches. We present our results on the Princeton 3D Shape Benchmark database (1814 3D-models). Our 3D-model search engine is available on-line to assess and test our results. To our knowledge the FOX-MIIRE search engine is the first search engine that accepts 3D-models retrieval from photos [5]. The FOX-MIIRE search engine adapts its own user interface depending on the web access device (desktop computer, PDA, SmartPhone).

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