Paper Info
Title
Performance evaluation of face recognition algorithms on Asian face database
Abstract
Human face is one of the most common and useful keys to a person's identity. Although, a number of face recognition algorithms have been proposed, many researchers believe that the technology should be improved further in order to overcome the instability due to variable illuminations, expressions, poses and accessories. In general, face databases for European and American such as CMU PIE (USA), FERET (USA), AR Face DB (USA) and XM2VTS (UK) have been used for training face recognition algorithms and testing the performance of those. However, many of the images in databases are not adequately annotated with the exact pose angle, illumination angle and illuminant color. Also, the faces on these databases have definitely different characteristics from those of Asian. Thus, we constructed the well-designed Korean face database (KFDB), which includes not only images but also ground truth information for facial feature points, and description files for subjects and exact capture environments. In this paper, we report the experimental results of face recognition performed using CM (correlation matching), PCA (principal component analysis) and LFA (local feature analysis) algorithms under various conditions on the KFDB.
Year
DOI
Venue
2004
10.1109/AFGR.2004.1301544
FGR
Keywords
Field
DocType
face recognition algorithm,face recognition algorithms,local feature analysis,correlation matching,face recognition,pose angle,visual databases,exact capture environment,ar face db,illumination angle,feature extraction,training face recognition algorithm,asian face database,performance evaluation,illuminant color,face databases,human face,principal component analysis,correlation methods,facial feature points,testing,algorithm design and analysis,lighting,ground truth
Illumination angle,Expression (mathematics),Computer science,Artificial intelligence,Face detection,Computer vision,Facial recognition system,Pattern recognition,Three-dimensional face recognition,Feature extraction,Ground truth,Database,Principal component analysis
Conference
ISBN
Citations 
PageRank 
0-7695-2122-3
11
0.91
References 
Authors
4
3
Name
Order
Citations
PageRank
Bon-Woo Hwang117716.33
Myung-Cheol Roh212910.71
Seong-Whan Lee33756343.90