An image-based approach to visual feature space analysis

16th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG'2008 - In Co-operation with EUROGRAPHICS, Full Papers

Volumn , Issue , 2008, Pages 223-230

  Schreck, Tobias ^a   Schneidewind, Jörn ^b   Keim, Daniel A ^b  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

^b UNIVERSITY OF KONSTANZ   (Germany)

Author keywords

Automatic feature selection; Feature vectors; Self organizing maps; Visual analytics

Indexed keywords

AUTOMATIC FEATURE SELECTION; COMPLEX DATA; DATA DEPENDENT; DATA ELEMENTS; DATA TYPE; FEATURE SELECTION PROBLEM; FEATURE SPACE; FEATURE VECTORS; IMAGE-BASED; IMAGE-BASED ANALYSIS; INTELLIGENT DATA ANALYSIS; NUMERIC VALUES; POWER ANALYSIS; SIMILARITY SCORES; SIMILARITY SEARCH; VISUAL ANALYTICS; VISUAL FEATURE;

CLUSTERING ALGORITHMS; COMPUTER GRAPHICS; CONFORMAL MAPPING; VECTORS; VISUALIZATION;

COMPUTER VISION;

EID: 84861313872     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. C. Aggarwal. On the effects of dimensionality reduction on high dimensional similarity search. In Proceedings of the ACM Symposium on Principles of Database Systems, 2001.
2. R. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley, 1999.
3. B. Bustos, D. Keim, D. Saupe, T. Schreck, and D. Vranić. Feature-based similarity search in 3D object databases. ACM Computing Surveys, 37:345-387, 2005.
4. B. Bustos, D. Keim, D. Saupe, T. Schreck, and D. Vranic. An experimental effectiveness comparison of methods for 3D similarity search. International Journal on Digital Libraries, Special Issue on Multimedia Contents and Management, 6(1):39- 54, 2006.
5. R. Duda, P. Hart, and D. Stork. Pattern Classification. Wiley-Interscience, New York, 2nd edition, 2001.
6. M.D. Esteban and D. Morales. A summary of entropy statistics. Kybernetika, 31(4):337-346, 1995.
7. R. Gonzalez and R. Woods. Digital Image Processing. Prentice Hall, 3rd edition, 2008.
8. J. Han and M. Kamber. Data Mining: Concepts and Techniques. Morgan Kauffman, 2nd edition, 2006.
9. A. Hinneburg, C. Aggarwal, and D. Keim. What is the nearest neighbor in high dimensional spaces? In Proceedings of the International Conference on Very Large Data Bases, 2000.
10. T. Kohonen. Self-Organizing Maps. Springer, Berlin, 3rd edition, 2001.
11. 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.
12. T. Schreck, D. Fellner, and D. Keim. Towards automatic feature vector optimization for multimedia applications. In Proceedings of the ACM Symposium on Applied Computing, Multimedia and Visualization track, 2008. To appear.
13. T. Schreck, D. Keim, and C. Panse. Visual feature space analysis for unsupervised effectiveness estimation and feature engineering. In Proceedings of the IEEE International Conference on Multimedia and Expo, 2006.
14. P. Shilane, P. Min, M. Kazhdan, and T. Funkhouser. The princeton shape benchmark. In Proceedings of the International Conference on Shape Modeling and Applications, 2004.
15. J. Vesanto. SOM-based data visualization methods. Intelligent Data Analysis, 3(2):111-126, 1999.