ACM Transactions on Graphics (TOG)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
SMI '04 Proceedings of the Shape Modeling International 2004
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
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
A spectral approach to shape-based retrieval of articulated 3D models
Computer-Aided Design
Pose-Oblivious Shape Signature
IEEE Transactions on Visualization and Computer Graphics
Partial matching of 3D shapes with priority-driven search
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Laplace-Beltrami eigenfunctions for deformation invariant shape representation
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids
Computer-Aided Design
A concise and provably informative multi-scale signature based on heat diffusion
SGP '09 Proceedings of the Symposium on Geometry Processing
Exploring the bag-of-words method for 3D shape retrieval
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Blind and robust mesh watermarking using manifold harmonics
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Spectral-Driven Isometry-Invariant Matching of 3D Shapes
International Journal of Computer Vision
International Journal of Computer Vision
ACM SIGGRAPH 2010 Courses
Visual Similarity Based 3D Shape Retrieval Using Bag-of-Features
SMI '10 Proceedings of the 2010 Shape Modeling International Conference
Parallel Poisson disk sampling with spectrum analysis on surfaces
ACM SIGGRAPH Asia 2010 papers
Shape google: Geometric words and expressions for invariant shape retrieval
ACM Transactions on Graphics (TOG)
3D-Shape Retrieval Using Curves and HMM
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Least squares quantization in PCM
IEEE Transactions on Information Theory
Characterizing shape using conformal factors
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
3D object retrieval using an efficient and compact hybrid shape descriptor
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
Visual vocabulary signature for 3D object retrieval and partial matching
EG 3DOR'09 Proceedings of the 2nd Eurographics conference on 3D Object Retrieval
Feature selection for enhanced spectral shape comparison
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
A comparison of methods for non-rigid 3D shape retrieval
Pattern Recognition
SP-Dock: Protein-Protein Docking Using Shape and Physicochemical Complementarity
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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This paper presents a 3D shape retrieval algorithm based on the Bag of Words (BoW) paradigm. For a given 3D shape, the proposed approach considers a set of feature points uniformly sampled on the surface and associated with local Fourier descriptors; this descriptor is computed in the neighborhood of each feature point by projecting the geometry onto the eigenvectors of the Laplace-Beltrami operator, it is highly discriminative, robust to connectivity and geometry changes and also fast to compute. In a preliminary step, a visual dictionary is built by clustering a large set of feature descriptors, then each 3D shape is described by an histogram of occurrences of these visual words. The performances of our approach have been compared against very recent state-of-theart methods on several different datasets. For global shape retrieval our approach is comparable to these recent works, however it clearly outperforms them in the case of partial shape retrieval.