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Proceedings Paper

An overview of view-based 2D/3D indexing methods
Author(s): Raluca-Diana Petre; Titus Zaharia; Françoise Prêteux
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Paper Abstract

This paper proposes a comprehensive overview of state of the art 2D/3D, view-based indexing methods. The principle of 2D/3D indexing methods consists of describing 3D models by means of a set of 2D shape descriptors, associated with a set of corresponding 2D views (under the assumption of a given projection model). Notably, such an approach makes it possible to identify 3D objects of interest from 2D images/videos. An experimental evaluation is also proposed, in order to examine the influence of the number of views and of the associated viewing angle selection strategies on the retrieval results. Experiments concern both 3D model retrieval and image recognition from a single view. Results obtained show promising performances, with recognition rates from a single view higher then 66%, which opens interesting perspectives in terms of semantic metadata extraction from still images/videos.

Paper Details

Date Published: 23 August 2010
PDF: 12 pages
Proc. SPIE 7799, Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII, 779904 (23 August 2010); doi: 10.1117/12.861542
Show Author Affiliations
Raluca-Diana Petre, Institut Télécom, Télécom SudParis, CNRS (France)
Titus Zaharia, Institut Télécom, Télécom SudParis, CNRS (France)
Françoise Prêteux, Mines ParisTech (France)

Published in SPIE Proceedings Vol. 7799:
Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII
Mark S. Schmalz; Gerhard X. Ritter; Junior Barrera; Jaakko T. Astola, Editor(s)

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