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Indexation multi-vues et recherche d'objets 3D

Abstract : In this thesis, we focus on issues related to 3D objects indexing and content based retrieval. Particularly, we focused on multi-view indexing methods. These approaches, characterized the shape by using 2D projections of the 3D object. First, we introduce a new approach to normalize and align the 3D objects necessary for our indexing process. The definition of position and scale is based on the minimal bounding sphere that offers interesting properties for our multi-view characterization of the shape. To find an optimal alignment for the objects, we propose an estimator based on results obtained in cognitive psychology to compare two different poses. In a second part, we define three new shape descriptors based on 2D projections. The first describes the shape of a silhouette with a set of pixels. This allows using set operators to compare signatures. In a second step, we use convexities and concavities information to describe the contour of the projections of our 3D objects. With these measures we have defined two related descriptors based on histograms and DCT compression. Finally, we propose a last descriptor where 2D projections are associated with orientation surface information. This "normal map" descriptor is compressed using Fourier coefficients. Finally, our retrieval process can query the database using 3D objects, pictures or sketches. To ensure effective search in time and relevance of results, we propose two optimizations. The first is based on results fusion using different aggregation operators while the latter quickly eliminates distant objects to the query through an early pruning.
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Submitted on : Tuesday, March 15, 2011 - 10:43:21 PM
Last modification on : Monday, June 27, 2022 - 3:05:17 AM
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  • HAL Id : pastel-00576966, version 1


Thibault Napoléon. Indexation multi-vues et recherche d'objets 3D. Traitement des images [eess.IV]. Télécom ParisTech, 2010. Français. ⟨pastel-00576966⟩



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