Multiple Data-Dependent Kernel Fisher Discriminant Analysis for Face Recognition
Joint Authors
Li, Yi-bing
Liu, Dandan
Liu, Yue
Xie, Hong
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-06
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Kernel Fisher discriminant analysis (KFDA) method has demonstrated its success in extracting facial features for face recognition.
Compared to linear techniques, it can better describe the complex and nonlinear variations of face images.
However, a single kernel is not always suitable for the applications of face recognition which contain data from multiple, heterogeneous sources, such as face images under huge variations of pose, illumination, and facial expression.
To improve the performance of KFDA in face recognition, a novel algorithm named multiple data-dependent kernel Fisher discriminant analysis (MDKFDA) is proposed in this paper.
The constructed multiple data-dependent kernel (MDK) is a combination of several base kernels with a data-dependent kernel constraint on their weights.
By solving the optimization equation based on Fisher criterion and maximizing the margin criterion, the parameter optimization of data-dependent kernel and multiple base kernels is achieved.
Experimental results on the three face databases validate the effectiveness of the proposed algorithm.
American Psychological Association (APA)
Liu, Yue& Li, Yi-bing& Xie, Hong& Liu, Dandan. 2014. Multiple Data-Dependent Kernel Fisher Discriminant Analysis for Face Recognition. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-506483
Modern Language Association (MLA)
Liu, Yue…[et al.]. Multiple Data-Dependent Kernel Fisher Discriminant Analysis for Face Recognition. Mathematical Problems in Engineering No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-506483
American Medical Association (AMA)
Liu, Yue& Li, Yi-bing& Xie, Hong& Liu, Dandan. Multiple Data-Dependent Kernel Fisher Discriminant Analysis for Face Recognition. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-506483
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-506483