Structure-adaptive SOM to classify 3-dimensional point light actors' gender

Sung Bae Cho

doi:10.1109/ICONIP.2002.1198201

Structure-adaptive SOM to classify 3-dimensional point light actors' gender

Sung Bae Cho

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Classifying the patterns of moving point lights attached on actor's bodies with self-organizing map often fails to get successful results with its original unsupervised learning algorithm. This paper exploits a structure-adaptive self-organizing map (SASOM) which adaptively updates the weights, structure and size of the map, resulting in remarkable improvement of pattern classification performance. We have compared the results with those of conventional pattern classifiers and human subjects. SASOM turns out to be the best classifier producing 97.1% of recognition rate on the 312 test data from 26 subjects.

Original language	English
Title of host publication	ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing
Subtitle of host publication	Computational Intelligence for the E-Age
Editors	Lipo Wang, Jagath C. Rajapakse, Kunihiko Fukushima, Soo-Young Lee, Xin Yao
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	549-553
Number of pages	5
ISBN (Electronic)	9810475241, 9789810475246
DOIs	https://doi.org/10.1109/ICONIP.2002.1198201
Publication status	Published - 2002
Event	9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore Duration: 2002 Nov 18 → 2002 Nov 22

Publication series

Name	ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
Volume	2

Other

Other	9th International Conference on Neural Information Processing, ICONIP 2002
Country	Singapore
City	Singapore
Period	02/11/18 → 02/11/22

Bibliographical note

Funding Information:
This paper was supported by Brain Science and Engineering Research Program sponsored by Korean Ministry of Science and Technology.

Publisher Copyright:
© 2002 Nanyang Technological University.

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Information Systems
Signal Processing

Access to Document

10.1109/ICONIP.2002.1198201

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Cho, S. B. (2002). Structure-adaptive SOM to classify 3-dimensional point light actors' gender. In L. Wang, J. C. Rajapakse, K. Fukushima, S-Y. Lee, & X. Yao (Eds.), ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age (pp. 549-553). [1198201] (ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICONIP.2002.1198201

Cho, Sung Bae. / Structure-adaptive SOM to classify 3-dimensional point light actors' gender. ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. editor / Lipo Wang ; Jagath C. Rajapakse ; Kunihiko Fukushima ; Soo-Young Lee ; Xin Yao. Institute of Electrical and Electronics Engineers Inc., 2002. pp. 549-553 (ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age).

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title = "Structure-adaptive SOM to classify 3-dimensional point light actors' gender",

abstract = "Classifying the patterns of moving point lights attached on actor's bodies with self-organizing map often fails to get successful results with its original unsupervised learning algorithm. This paper exploits a structure-adaptive self-organizing map (SASOM) which adaptively updates the weights, structure and size of the map, resulting in remarkable improvement of pattern classification performance. We have compared the results with those of conventional pattern classifiers and human subjects. SASOM turns out to be the best classifier producing 97.1% of recognition rate on the 312 test data from 26 subjects.",

author = "Cho, {Sung Bae}",

note = "Funding Information: This paper was supported by Brain Science and Engineering Research Program sponsored by Korean Ministry of Science and Technology. Publisher Copyright: {\textcopyright} 2002 Nanyang Technological University.; 9th International Conference on Neural Information Processing, ICONIP 2002 ; Conference date: 18-11-2002 Through 22-11-2002",

year = "2002",

doi = "10.1109/ICONIP.2002.1198201",

language = "English",

series = "ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "549--553",

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Cho, SB 2002, Structure-adaptive SOM to classify 3-dimensional point light actors' gender. in L Wang, JC Rajapakse, K Fukushima, S-Y Lee & X Yao (eds), ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age., 1198201, ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age, vol. 2, Institute of Electrical and Electronics Engineers Inc., pp. 549-553, 9th International Conference on Neural Information Processing, ICONIP 2002, Singapore, Singapore, 02/11/18. https://doi.org/10.1109/ICONIP.2002.1198201

Structure-adaptive SOM to classify 3-dimensional point light actors' gender. / Cho, Sung Bae.

ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. ed. / Lipo Wang; Jagath C. Rajapakse; Kunihiko Fukushima; Soo-Young Lee; Xin Yao. Institute of Electrical and Electronics Engineers Inc., 2002. p. 549-553 1198201 (ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Classifying the patterns of moving point lights attached on actor's bodies with self-organizing map often fails to get successful results with its original unsupervised learning algorithm. This paper exploits a structure-adaptive self-organizing map (SASOM) which adaptively updates the weights, structure and size of the map, resulting in remarkable improvement of pattern classification performance. We have compared the results with those of conventional pattern classifiers and human subjects. SASOM turns out to be the best classifier producing 97.1% of recognition rate on the 312 test data from 26 subjects.

AB - Classifying the patterns of moving point lights attached on actor's bodies with self-organizing map often fails to get successful results with its original unsupervised learning algorithm. This paper exploits a structure-adaptive self-organizing map (SASOM) which adaptively updates the weights, structure and size of the map, resulting in remarkable improvement of pattern classification performance. We have compared the results with those of conventional pattern classifiers and human subjects. SASOM turns out to be the best classifier producing 97.1% of recognition rate on the 312 test data from 26 subjects.

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Cho SB. Structure-adaptive SOM to classify 3-dimensional point light actors' gender. In Wang L, Rajapakse JC, Fukushima K, Lee S-Y, Yao X, editors, ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. Institute of Electrical and Electronics Engineers Inc. 2002. p. 549-553. 1198201. (ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age). https://doi.org/10.1109/ICONIP.2002.1198201

Structure-adaptive SOM to classify 3-dimensional point light actors' gender

Abstract

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Bibliographical note

All Science Journal Classification (ASJC) codes

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