Locally Linear Discriminate Embedding for Face Recognition
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-01-05
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A novel method based on the local nonlinear mapping is presented in this research.
The method is called Locally Linear Discriminate Embedding (LLDE).
LLDE preserves a local linear structure of a high-dimensional space and obtains a compact data representation as accurately as possible in embedding space (low dimensional) before recognition.
For computational simplicity and fast processing, Radial Basis Function (RBF) classifier is integrated with the LLDE.
RBF classifier is carried out onto low-dimensional embedding with reference to the variance of the data.
To validate the proposed method, CMU-PIE database has been used and experiments conducted in this research revealed the efficiency of the proposed methods in face recognition, as compared to the linear and non-linear approaches.
American Psychological Association (APA)
Abusham, Eimad E.& Wong, E. K.. 2010. Locally Linear Discriminate Embedding for Face Recognition. Discrete Dynamics in Nature and Society،Vol. 2009, no. 2009, pp.1-8.
https://search.emarefa.net/detail/BIM-507848
Modern Language Association (MLA)
Abusham, Eimad E.& Wong, E. K.. Locally Linear Discriminate Embedding for Face Recognition. Discrete Dynamics in Nature and Society No. 2009 (2009), pp.1-8.
https://search.emarefa.net/detail/BIM-507848
American Medical Association (AMA)
Abusham, Eimad E.& Wong, E. K.. Locally Linear Discriminate Embedding for Face Recognition. Discrete Dynamics in Nature and Society. 2010. Vol. 2009, no. 2009, pp.1-8.
https://search.emarefa.net/detail/BIM-507848
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-507848