Comparison of Eigenface-Based Feature Vectors under Different Impairments

Cambridge UK August 23-August 26

DOI Bookmark:

http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334111

17th International Conference on Patt ...

	This Article
	PURCHASE ARTICLE: $19 PDF HTML IEEE Xplore Subscribers
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Aristodemos Pnevmatikakis Articles by Lazaros Polymenakos

	ASCII Text	x
	Aristodemos Pnevmatikakis, Lazaros Polymenakos, "Comparison of Eigenface-Based Feature Vectors under Different Impairments," Pattern Recognition, International Conference on, vol. 1, pp. 296-299, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004.

	BibTex	x
	@article{ 10.1109/ICPR.2004.1334111, author = {Aristodemos Pnevmatikakis and Lazaros Polymenakos}, title = {Comparison of Eigenface-Based Feature Vectors under Different Impairments}, journal ={Pattern Recognition, International Conference on}, volume = {1}, year = {2004}, issn = {1051-4651}, pages = {296-299}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334111}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - Comparison of Eigenface-Based Feature Vectors under Different Impairments SN - 1051-4651 SP296 EP299 A1 - Aristodemos Pnevmatikakis, A1 - Lazaros Polymenakos, PY - 2004 KW - null VL - 1 JA - Pattern Recognition, International Conference on ER -

Aristodemos Pnevmatikakis, Athens Information Technology Institute, Greece

Lazaros Polymenakos, Athens Information Technology Institute, Greece

We study the performance of a new eigenface-based method for face recognition. Specifically, we perform DCT preprocessing followed by the PCA-LDA combination. We compare the new method to existing ones (PCA, PCA-LDA, DCT-PCA) under impairments like changes in brightness, direction-of-illumination, hairstyle, clothing, expression, head orientation, and added noise.

Citation:

Aristodemos Pnevmatikakis, Lazaros Polymenakos, "Comparison of Eigenface-Based Feature Vectors under Different Impairments," icpr, vol. 1, pp.296-299, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.