6,635 research outputs found
Salient Local 3D Features for 3D Shape Retrieval
In this paper we describe a new formulation for the 3D salient local features
based on the voxel grid inspired by the Scale Invariant Feature Transform
(SIFT). We use it to identify the salient keypoints (invariant points) on a 3D
voxelized model and calculate invariant 3D local feature descriptors at these
keypoints. We then use the bag of words approach on the 3D local features to
represent the 3D models for shape retrieval. The advantages of the method are
that it can be applied to rigid as well as to articulated and deformable 3D
models. Finally, this approach is applied for 3D Shape Retrieval on the McGill
articulated shape benchmark and then the retrieval results are presented and
compared to other methods.Comment: Three-Dimensional Imaging, Interaction, and Measurement. Edited by
Beraldin, J. Angelo; Cheok, Geraldine S.; McCarthy, Michael B.;
Neuschaefer-Rube, Ulrich; Baskurt, Atilla M.; McDowall, Ian E.; Dolinsky,
Margaret. Proceedings of the SPIE, Volume 7864, pp. 78640S-78640S-8 (2011).
Conference Location: San Francisco Airport, California, USA ISBN:
9780819484017 Date: 10 March 201
Data-Driven Shape Analysis and Processing
Data-driven methods play an increasingly important role in discovering
geometric, structural, and semantic relationships between 3D shapes in
collections, and applying this analysis to support intelligent modeling,
editing, and visualization of geometric data. In contrast to traditional
approaches, a key feature of data-driven approaches is that they aggregate
information from a collection of shapes to improve the analysis and processing
of individual shapes. In addition, they are able to learn models that reason
about properties and relationships of shapes without relying on hard-coded
rules or explicitly programmed instructions. We provide an overview of the main
concepts and components of these techniques, and discuss their application to
shape classification, segmentation, matching, reconstruction, modeling and
exploration, as well as scene analysis and synthesis, through reviewing the
literature and relating the existing works with both qualitative and numerical
comparisons. We conclude our report with ideas that can inspire future research
in data-driven shape analysis and processing.Comment: 10 pages, 19 figure
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