Paper Info
Title
Performance evaluation of face recognition algorithms on the asian face database, KFDB
Abstract
Human face is one of the most common and useful keys to a person's identity. Many algorithms have been developed for automatic face recognition. And a number of commercial products have reached the market already. In general, however, many believe that the technology has yet to improve further, particularly to overcome the instability due to variable illuminations, expressions, poses and accessories. These variations often lead to large nonlinear variation in facial image. To date it is a very important issue to understand the limitation of the current face recognition technology. In this paper, we report the experimental result of face recognition performed using PCA (Principal Component Analysis), LFA(Local Feature Analysis) and correlation matching algorithms on the KFDB(Korean Face Database) which contains Korean face images taken under various conditions.
Year
Venue
Keywords
2003
AVBPA
asian face database,human face,face recognition,automatic face recognition,principal component analysis,korean face database,performance evaluation,current face recognition technology,face recognition algorithm,commercial product,local feature analysis,korean face image
Field
DocType
Volume
Facial recognition system,Face hallucination,Expression (mathematics),Three-dimensional face recognition,Computer science,Face Recognition Grand Challenge,Face detection,Biometrics,Principal component analysis,Database
Conference
2688
ISSN
ISBN
Citations 
0302-9743
3-540-40302-7
11
PageRank 
References 
Authors
0.76
4
4
Name
Order
Citations
PageRank
Bon-Woo Hwang117716.33
Hyeran Byun250565.97
Myoung-Cheol Roh3110.76
Seong-Whan Lee43756343.90