3D shape similarity using vectors of locally aggregated tensors
Date
2013
Authors
Tabia, H.
Picard, D.
Laga, H.
Gosselin, P.H.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
2013 IEEE International Conference on Image Processing: ICIP 2013 Proceedings, 2013, pp.2694-2698
Statement of Responsibility
Conference Name
2013 IEEE International Conference on Image Processing (15 Sep 2013 - 18 Sep 2013 : Melbourne, Australia)
Abstract
In this paper, we present an efficient 3D object retrieval method invariant to scale, orientation and pose. Our approach is based on the dense extraction of discriminative local descriptors extracted from 2D views. We aggregate the descriptors into a single vector signature using tensor products. The similarity between 3D models can then be efficiently computed with a simple dot product. Experiments on the SHREC12 commonly-used benchmark demonstrate that our approach obtains superior performance in searching for generic shapes.
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Dissertation Note
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Description
Link to a related website: http://hal.inria.fr/docs/00/83/21/82/PDF/tabia13icip.pdf, Open Access via Unpaywall
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Copyright 2013 IEEE