Hand gesture recognition: Self-organising maps as a graphical user interface for the partitioning of large training data sets

Proceedings - International Conference on Pattern Recognition

Volumn 4, Issue , 2004, Pages 581-584

  Heidemann, Gunther ^a   Bekel, Holger ^a   Bax, Ingo ^a   Saalbach, Axel ^a  

^a BIELEFELD UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DATA ACQUISITION; DEGREES OF FREEDOM (MECHANICS); GRAPHICAL USER INTERFACES; HUMAN COMPUTER INTERACTION; PERSONNEL TRAINING; PROBLEM SOLVING; SELF ORGANIZING MAPS;

APPEARANCE BASED REPRESENTATION; DATA SETS; NEURAL CLASSIFICATION SYSTEMS; SELF-OCCLUSION;

GESTURE RECOGNITION;

EID: 10044292739     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2004.1333817     Document Type: Conference Paper

References (17)

1. S. C. Ahalt, A. K. Krisnamurthy, P. Chen, and D. E. Melton. Competitive learning algorithms for vector quantization. Neural Networks, 3:277-290, 1990.
2. C. Bregler and S. M. Omohundro. Surface Learning with Applications to Lipreading. In J. Cowan, G. Tesauro, and J. Alspector, editors, Advances in Neural Information Processing Systems 1993, volume 6, pages 43-50. Morgan-Kaufmann Publishers, 1994.
3. S. Grossberg. Competitive learning: From interactive activation to adaptive resonance. Cognitive Sci., 11:23-63, 1987.
4. C. Harris and M. Stephens. A Combined Corner and Edge Detector. In Proc. 4th Alvey Vision Conf., pages 147-151, 1988.
5. G. Heidemann, D. Lücke, and H. Ritter. A System for Various Visual Classification Tasks Based on Neural Networks. In A. S. et al., editor, Proc. 15th Int'l Conf. on Pattern Recognition ICPR 2000, Barcelona, volume I, pages 9-12, 2000.
6. G. Heidemann, R. Rae, H. Bekel, I. Bax, and H. Ritter. Integrating context-free and context-dependent attentional mechanisms for gestural object reference. In Proc. ICVS 03, pages 22-33, Graz, Austria, 2003.
7. G. Heidemann and H. Ritter. Efficient Vector Quantization Using the WTA-rule with Activity Equalization. Neural Processing Letters, 13(1):17-30, 2001.
8. G. E. Hinton, P. Dayan, and M. Revow. Modelling the Manifolds of Images of Handwritten Digits. IEEE Trans. on Neural Networks, 8(1):65-74, 1997.
9. N. Kambhatla and T. K. Leen. Fast Non-Linear Dimension Reduction. In J. Cowan, G. Tesauro, and J. Alspector, editors, Advances in Neural Information Processing Systems 1993, volume 6, pages 152-159. Morgan Kaufmann Publishers, 1994.
10. T. Kohonen. Self-Organizing Maps. Springer Verlag, 1995.
11. B. Moghaddam and A. Pentland. Probabilistic Visual Learning for Object Representation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(7):696-710, 1997.
12. H. Murase and S. K. Nayar. Visual Learning and Recognition of 3-D Objects from Appearance. Int'l J. of Computer Vision, 14:5-24, 1995.
13. D. Reisfeld, H. Wolfson, and Y. Yeshurun. Context-Free Attentional Operators: The Generalized Symmetry Transform. Int'l J. of Computer Vision, 14:119-130, 1995.
14. H. J. Ritter, T. M. Martinetz, and K. J. Schulten. Neuronale Netze. Addison-Wesley, München, 1992.
15. A. Saalbach. Self-Organizing Maps zur halbautomatischen Erzeugung datennaher Klasseneinteilungen. Master's thesis, Univ. Bielefeld, Technische Fakultät, 2001.
16. T. D. Sanger. Optimal Unsupervised Learning in a Single-Layer Linear Feedforward Neural Network. Neural Networks, 2:459-473, 1989.
17. M. E. Tipping and C. M. Bishop. Mixtures of probabilistic principal component analyzers. Neural Computation, 11(2):443-482, 1999.