2D Maps for Visual Analysis and Retrieval in Large Multi-Feature 3D Model Databases
Page 598.2
Abstract
Multimedia objects are often described by high-dimensional feature vectors which can be used for retrieval and clustering tasks. We have built an interactive retrieval system for 3D model databases that implements a variety of different feature transforms. Recently, we have enhanced the functionality of our system by integrating a SOM-based visualization module. In this poster demo, we show how 2D maps can be used to improve the effectiveness of retrieval, clustering, and over-viewing tasks in a 3D multimedia system.
References
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B. Bustos, D. Keim, D. Saupe, T. Schreck, and D. Vrani¿. Using entropy impurity for improved 3d object similarity search. In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME'04), 2004.
[2]
T. Kohonen, J. Hynninen, J. Kangas, and J. Laaksonen. Som_pak: The self-organizing map program package. Technical Report A31, Helsinki University of Technology, Laboratory of Computer and Information Science, 1996.
[3]
T. Kohonen. Self-Organizing Maps. Springer, Berlin, 3rd edition, 2001.
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E. Pampalk, A. Rauber, and D. Merkl. Using smoothed data histograms for cluster visualization in self-organizing maps. In Proc. Int. Conf. on Artifical Neural Networks (ICANN'02), volume 2415 of Lecture Notes in Computer Science. Springer, 2002.
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J. Tangelder and R. Veltkamp. A survey of content based 3d shape retrieval methods. In Proc. Shape Modeling International 2004 (SMI'04). IEEE CS Press, 2004.
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Published In
October 2004
667 pages
ISBN:0780387880
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IEEE Computer Society
United States
Publication History
Published: 10 October 2004
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