Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Transactions on Graphics (TOG)
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Survey of Content Based 3D Shape Retrieval Methods
SMI '04 Proceedings of the Shape Modeling International 2004
Deformation transfer for triangle meshes
ACM SIGGRAPH 2004 Papers
Shape-based retrieval and analysis of 3d models
Communications of the ACM - 3d hard copy
Selecting Distinctive 3D Shape Descriptors for Similarity Retrieval
SMI '06 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006
Probabilistic fingerprints for shapes
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Numerical Geometry of Non-Rigid Shapes
Numerical Geometry of Non-Rigid Shapes
Online dictionary learning for sparse coding
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids
Computer-Aided Design
Three-dimensional shape searching: state-of-the-art review and future trends
Computer-Aided Design
A concise and provably informative multi-scale signature based on heat diffusion
SGP '09 Proceedings of the Symposium on Geometry Processing
Online Learning for Matrix Factorization and Sparse Coding
The Journal of Machine Learning Research
International Journal of Computer Vision
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
Shape google: Geometric words and expressions for invariant shape retrieval
ACM Transactions on Graphics (TOG)
Statistical 3D Shape Analysis by Local Generative Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
SHREC'10 track: non-rigid 3D shape retrieval
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
SHREC 2011: robust feature detection and description benchmark
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
SHREC'11 track: shape retrieval on non-rigid 3D watertight meshes
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
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In 3D object retrieval it is very important to define reliable shape descriptors, which compactly characterize geometric properties of the underlying surface. To this aim two main approaches are considered: global, and local ones. Global approaches are effective in describing the whole object, while local ones are more suitable to characterize small parts of the shape. Some strategies to combine these two approaches have been proposed recently but still no consolidate work is available in this field. With this paper we address this problem and propose a new method based on sparse coding techniques. A set of local shape descriptors are collected from the shape. Then a dictionary is trained as generative model. In this fashion the dictionary is used as global shape descriptor for shape retrieval purposes. Preliminary experiments are performed on a standard dataset by showing a drastic improvement of the proposed method in comparison with well known local-to-global and global approaches.