Selecting typical instances in instance-based learning
ML92 Proceedings of the ninth international workshop on Machine learning
Organizing Large Structural Modelbases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topology matching for fully automatic similarity estimation of 3D shapes
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Discovering Useful Concept Prototypes for Classification Based on Filtering and Abstraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Survey of Content Based 3D Shape Retrieval Methods
SMI '04 Proceedings of the Shape Modeling International 2004
Automatic Class Selection and Prototyping for 3-D Object Classification
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
Parts-based 3D object classification
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Representation and classification of 3-D objects
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Reeb graphs for shape analysis and applications
Theoretical Computer Science
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
A Learning Approach to 3D Object Representation for Classification
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
From 2D silhouettes to 3D object retrieval: contributions and benchmarking
Journal on Image and Video Processing
Artificial Intelligence for Engineering Design, Analysis and Manufacturing - Representing and Reasoning About Three-Dimensional Space
A parts-based approach for automatic 3D shape categorization using belief functions
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems
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3D shape classification plays an important role in the process of organizing and retrieving models in large databases. Classifying shapes means to assign a query model to the most appropriate class of objects: knowledge about the membership of models to classes can be very useful to speed up and improve the shape retrieval process, by allowing the reduction of the candidate models to compare with the query. The main contribution of this paper is the setting of a framework to compare the effectiveness of different query-to-class membership measures, defined independently of specific shape descriptors. The classification performances are evaluated against a set of popular 3D shape descriptors, using a dataset consisting of 14 classes made up of 20 objects each.