3-D search
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praveenagnihotry
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Posts: 3
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#1
22-08-2010, 05:38 PM


Dear Sir,
am Praveen Agnihotry Pursuing B.Tech in INFORMATION
TECHNOLOGY from MGM'S C.O.E.T. Noida and my seminar and presentation
topic is 3-D Search So please send me complete power point
presentation and a copy of explanation of its presentation.
thanking you.
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#2
23-09-2010, 11:13 AM

More Info About 3-D search


some brief about

Abstract

The method for three-dimensional (3D)- model indexing based on two-dimensional (2D) views, which we call adaptive views clustering (AVC). The goal of this method is to provide an "optimal" selection of 2D views from a 3D model, and a probabilistic Bayesian method for 3D-model retrieval from these views. The characteristic view selection algorithm is based on an adaptive clustering algorithm and uses statistical model distribution scores to select the optimal number of views. Starting from the fact that all views do not have equal importance, we also introduce a novel Bayesian approach to improve the retrieval. Finally, we present our results and compare our method to some state-of-the-art 3D retrieval descriptors on the Princeton 3D Shape Benchmark database and a 3D-CAD-models database supplied by the car manufacturer Renault
refered by :::--
This paper appears in: Multimedia, IEEE Transactions on
Issue Date: Jan. 2007
Volume: 9 Issue:1
On page(s): 78 - 88
ISSN: 1520-9210
INSPEC Accession Number: 9236064
Digital Object Identifier: 10.1109/TMM.2006.886359
Date of Current Version: 19 December 2006
Sponsored by: IEEE Circuits & Systems Society IEEE Signal Processing Society IEEE Communications Society IEEE Computer Society





some other tips for About 3-D search


ABSTRACT

The size of 3-D data stored around the Web has become bigger. Therefore the development of recognition applications and retrieval systems of 3-D models is important. In this paper we propose a new scheme to measure similarity between 3-D models. The main idea is to reconstruct a 3-D closed curve that represents a 3-D model given by a polygonal mesh, and to extract a signature from this 3-D closed curve using the Fourier series. The proposed descriptor needs continuous principal component analysis (CPCA) to align 3-D models into a canonical position. The feature vectors constructed using this method, named Fourier series descriptor (FSD) are invariants under rigid transformations composed of translation, rotation, flipping and scale; robust to noise and level of detail. A 3-D polygonal mesh model serves as a query for search by shape similarity in a large collection of 3-D models database using an interactive 3-D search engine.

REFERENCESSource Computer Vision and Image Understanding archive
Volume 114 , Issue 1 (January 2010) table of contents
Pages: 1-7
Year of Publication: 2010
ISSN:1077-3142
Authors Elmustapha Ait Lmaati SIRC, Faculté des sciences Semlalia, Département Informatique, BP 2390, 40000, Marrakech, Morocco
Ahmed El Oirrak SIRC, Faculté des sciences Semlalia, Département Informatique, BP 2390, 40000, Marrakech, Morocco and Faculté des sciences, de Rabat, LEESA-GSCM, BP 1014, Rabat, Morocco
Driss Aboutajdine Faculté des sciences, de Rabat, LEESA-GSCM, BP 1014, Rabat, Morocco
Mohamed Daoudi Institut TELECOM; TELECOM Lille1; LIFL (UMR 8022), France
Mohammed Najib Kaddioui SIRC, Faculté des sciences Semlalia, Département Informatique, BP 2390, 40000, Marrakech, Morocco

Publisher Elsevier Science Inc. New York, NY, USA
Bibliometrics Downloads (6 Weeks): n/a, Downloads (12 Months): n/a, Citation Count: 0
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