A Head Gesture Recognition Method based on Eigenfaces using SOM and PRL 


Vol. 7,  No. 3, pp. 971-976, Mar.  2000
10.3745/KIPSTE.2000.7.3.971


PDF
  Abstract

In this paper a new method for head gesture recognition is proposed. At the first stage, face image data are transformed into low dimensional vectors by principal component analysis(PCA), which utilizes the high correlation between face pose images. Then a self organization map(SOM) is trained by the transformed face vectors, in such a that the nodes at similar locations respond to similar poses. A sequence of poses which comprises each model gesture goes through PCA and SOM, and the result is stored in the database. At the recognition stage any sequence of frames goes through the PCA and SOM, and the result is compared with the model gesture stored in the database. To improve robustness of classification, probabilistic relaxation labeling(PRL)is used, which utilizes the contextual information imbedded in the adjacent poses.

  Statistics
  Cite this article

[IEEE Style]

W. J. Lee and J. Y. Koo, "A Head Gesture Recognition Method based on Eigenfaces using SOM and PRL," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 7, no. 3, pp. 971-976, 2000. DOI: 10.3745/KIPSTE.2000.7.3.971.

[ACM Style]

Woo Jin Lee and Ja Young Koo. 2000. A Head Gesture Recognition Method based on Eigenfaces using SOM and PRL. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 7, 3, (2000), 971-976. DOI: 10.3745/KIPSTE.2000.7.3.971.

Forms

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)

Old Journals

Indexing

All publications of TKIPS is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.

TKIPS is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).

Related Journals