Visualising and clustering video data

Colin Fyfe, Wei Chuang Ooi, Hanseok Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM) [1]. But whereas the GTM is an extension of a mixture of experts, this model is an extension of a product of experts [6]. We show visualisation and clustering results on a data set composed of video data of lips uttering 5 Korean vowels and show that the new mapping achieves better results than the standard Self-Organizing Map.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages335-344
Number of pages10
Volume4881 LNCS
Publication statusPublished - 2007 Dec 1
Event8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007 - Birmingham, United Kingdom
Duration: 2007 Dec 162007 Dec 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4881 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007
CountryUnited Kingdom
CityBirmingham
Period07/12/1607/12/19

Fingerprint

Lip
Cluster Analysis
Clustering
Mixture of Experts
Self organizing maps
Self-organizing Map
Self-organizing
Visualization
Projection
Datasets
Model

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Fyfe, C., Ooi, W. C., & Ko, H. (2007). Visualising and clustering video data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4881 LNCS, pp. 335-344). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4881 LNCS).

Visualising and clustering video data. / Fyfe, Colin; Ooi, Wei Chuang; Ko, Hanseok.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4881 LNCS 2007. p. 335-344 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4881 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fyfe, C, Ooi, WC & Ko, H 2007, Visualising and clustering video data. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4881 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4881 LNCS, pp. 335-344, 8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007, Birmingham, United Kingdom, 07/12/16.
Fyfe C, Ooi WC, Ko H. Visualising and clustering video data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4881 LNCS. 2007. p. 335-344. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Fyfe, Colin ; Ooi, Wei Chuang ; Ko, Hanseok. / Visualising and clustering video data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4881 LNCS 2007. pp. 335-344 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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