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2014 (Vol. 7, Issue: 8)
Article Information:

New Technique for 3D Shape Retrieval in the Classified Databases

El Wardani Dadi and El Mostafa Daoudi
Corresponding Author:  El Wardani Dad 

Key words:  3D classified database, 3D content-based shape retrieval, representatives of classes, right class, , ,
Vol. 7 , (8): 1618-1622
Submitted Accepted Published
May 26, 2013 June 21, 2013 February 27, 2014
Abstract:

This study addresses the problem of 3D shape retrieval. While this problem is interesting and emerging as the size of 3D object databases grows rapidly, the main two issues the community has to focus on are: computational efficiency of 3D object retrieval and the quality of retrieval results. In this study we deal with the two considerations, especially the first one namely computational efficiency, by proposing a new technique to retrieve efficiently the 3D-objects in the classified databases which contains 3D objects of different categories. This technique can be coupled with any 3D retrieval method. In this study, we use the Clock Matching Bag-of-Features 3D retrieval method proposed by Lian et al. (2010) since it gives the best result comparing with several methods in particular the view based methods. Instead of systematically matching the object-query with all 3D objects of the target database, our approach restricts the pattern matching on a subset of “good candidates” (the most similar to the query). For a database classified in several classes the retrieval will be oriented to the right class that contains similar objects to the query. In this case, the matching process will be not systematically performed with all objects among the database, but only with objects of right class. Our key idea is to represent each class by one representative that will be used to orient the retrieval process to the right class. Experimental results illustrate the efficiency of our approach.
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  Cite this Reference:
El Wardani Dadi and El Mostafa Daoudi, 2014. New Technique for 3D Shape Retrieval in the Classified Databases.  Research Journal of Applied Sciences, Engineering and Technology, 7(8): 1618-1622.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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