SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
3D Shape Histograms for Similarity Search and Classification in Spatial Databases
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Efficient Indexing and Retrieval Scheme for VRML Database
ICDCSW '04 Proceedings of the 24th International Conference on Distributed Computing Systems Workshops - W7: EC (ICDCSW'04) - Volume 7
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Geometry Image Matching for Similarity Estimation of 3D Shapes
CGI '04 Proceedings of the Computer Graphics International
Automatic Selection and Combination of Descriptors for Effective 3D Similarity Search
ISMSE '04 Proceedings of the IEEE Sixth International Symposium on Multimedia Software Engineering
Feature Combination and Relevance Feedback for 3D Model Retrieval
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Extended gloss overlaps as a measure of semantic relatedness
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
The colour and texture - a novel image retrieval technology based on human vision
International Journal of Innovative Computing and Applications
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In this paper, we describe several 3D shape descriptors and integrate a textual descriptor with them for 3D model retrieval. We analyse five Shape-Feature Vector (FV) integration approaches, namely Pure FV Integration (PFI), Reduced FV Integration (RFI), Weight-Associated RFI (WRFI), Distance Integration (DI) and Rank Integration (RI). By running all possible-combinations of weighting factors on a training data set, the best weighting factor for each approach is obtained. Our experiments show that the best weighting factors improve the retrieval performance on not only the training data set, but also other data sets. This paper also shows that Distance Integration delivers the best retrieval effectiveness and Reduced FV Integration has the capability to deal with unknown query. In addition, the Distance Integration provides faster processing as it uses precomputed pair-wise distance and is more advantageous than PFI because of the dimension reduction. Hence, the use of both approaches (DI and RFI) is proposed. This paper also explains a use of the model file name as the only resource for text feature extraction. We study several textual similarity measures and then integrate multishape and text features into 3D model retrieval. Our experiments show that text feature can discriminate 3D models to each other in a certain degree of effectiveness, and integration text feature with multishape-feature improves retrieval effectiveness.