Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Topics: A Compact Representation and New Algorithms for 3D Partial Shape Retrieval
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Retrieving articulated 3-D models using medial surfaces
Machine Vision and Applications
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
Exploring the bag-of-words method for 3D shape retrieval
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Visual Similarity Based 3D Shape Retrieval Using Bag-of-Features
SMI '10 Proceedings of the 2010 Shape Modeling International Conference
The bag of words approach for retrieval and categorization of 3D objects
The Visual Computer: International Journal of Computer Graphics - Special Issue on 3D Object Retrieval 2009
Local visual patch for 3d shape retrieval
Proceedings of the ACM workshop on 3D object retrieval
Improving the fisher kernel for large-scale image classification
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Shape google: Geometric words and expressions for invariant shape retrieval
ACM Transactions on Graphics (TOG)
Combination of bag-of-words descriptors for robust partial shape retrieval
The Visual Computer: International Journal of Computer Graphics - 3DOR 2011
Aggregating Local Image Descriptors into Compact Codes
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D object retrieval using an efficient and compact hybrid shape descriptor
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
Retrieval of 3D articulated objects using a graph-based representation
EG 3DOR'09 Proceedings of the 2nd Eurographics conference on 3D Object Retrieval
SHREC'12 track: generic 3D shape retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
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During the last decade, a significant attention has been paid, by the computer vision and the computer graphics communities, to three dimensional (3D) object retrieval. Shape retrieval methods can be divided into three main steps: the shape descriptors extraction, the shape signatures and their associated similarity measures, and the machine learning relevance functions. While the first and the last points have vastly been addressed in recent years, in this paper, we focus on the second point; presenting a new 3D object retrieval method using a new coding/pooling technique and powerful 3D shape descriptors extracted from 2D views. For a given 3D shape, the approach extracts a very large and dense set of local descriptors. From these descriptors, we build a new shape signature by aggregating tensor products of visual descriptors. The similarity between 3D models can then be efficiently computed with a simple dot product. We further improve the compactness and discrimination power of the descriptor using local Principal Component Analysis on each cluster of descriptors. Experiments on the SHREC 2012 and the McGill benchmarks show that our approach outperforms the state-of-the-art techniques, including other BoF methods, both in compactness of the representation and in the retrieval performance.