Application of non-Negative and Local non Negative Matrix Factorization to Facial Expression Recognition

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17th International Conference on Pattern Recognition (ICPR'04) - Volume 1

Cambridge UK

August 23-August 26

ISBN: 0-7695-2128-2

	ASCII Text	x
	Ioan Buciu, Ioannis Pitas, "Application of non-Negative and Local non Negative Matrix Factorization to Facial Expression Recognition," Pattern Recognition, International Conference on, vol. 1, pp. 288-291, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004.

	BibTex	x
	@article{ 10.1109/ICPR.2004.1334109, author = {Ioan Buciu and Ioannis Pitas}, title = {Application of non-Negative and Local non Negative Matrix Factorization to Facial Expression Recognition}, journal ={Pattern Recognition, International Conference on}, volume = {1}, year = {2004}, issn = {1051-4651}, pages = {288-291}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334109}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - Application of non-Negative and Local non Negative Matrix Factorization to Facial Expression Recognition SN - 1051-4651 SP288 EP291 A1 - Ioan Buciu, A1 - Ioannis Pitas, PY - 2004 KW - null VL - 1 JA - Pattern Recognition, International Conference on ER -

Ioan Buciu, Aristotle University of Thessaloniki, Greece

Ioannis Pitas, Aristotle University of Thessaloniki, Greece

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334109

In this paper two image representation approaches called non-negative matrix factorization (NMF) and local non-negative matrix factorization (LNMF) have been applied to two facial databases for recognizing six basic facial expressions. A principal component analysis (PCA) approach was performed as well for facial expression recognition for comparison purposes. We found that, for the first database, LNMF outperforms both PCA and NMF, while NMF produces the poorest recognition performance. Results are approximately the same for the second database, with slightly performance improvement on behalf of NMF.

Citation:

Ioan Buciu, Ioannis Pitas, "Application of non-Negative and Local non Negative Matrix Factorization to Facial Expression Recognition," icpr, vol. 1, pp.288-291, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004

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