Incremental Graph Regulated Nonnegative Matrix Factorization for Face Recognition
Joint Authors
Yu, Zhe-Zhou
Jia, Cheng-Cheng
Li, Bin
Pang, Shu-Chao
Liu, Yu-Hao
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-18
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In a real world application, we seldom get all images at one time.
Considering this case, if a company hired an employee, all his images information needs to be recorded into the system; if we rerun the face recognition algorithm, it will be time consuming.
To address this problem, In this paper, firstly, we proposed a novel subspace incremental method called incremental graph regularized nonnegative matrix factorization (IGNMF) algorithm which imposes manifold into incremental nonnegative matrix factorization algorithm (INMF); thus, our new algorithm is able to preserve the geometric structure in the data under incremental study framework; secondly, considering we always get many face images belonging to one person or many different people as a batch, we improved our IGNMF algorithms to Batch-IGNMF algorithms (B-IGNMF), which implements incremental study in batches.
Experiments show that (1) the recognition rate of our IGNMF and B-IGNMF algorithms is close to GNMF algorithm while it runs faster than GNMF.
(2) The running times of our IGNMF and B-IGNMF algorithms are close to INMF while the recognition rate outperforms INMF.
(3) Comparing with other popular NMF-based face recognition incremental algorithms, our IGNMF and B-IGNMF also outperform then both the recognition rate and the running time.
American Psychological Association (APA)
Yu, Zhe-Zhou& Liu, Yu-Hao& Li, Bin& Pang, Shu-Chao& Jia, Cheng-Cheng. 2014. Incremental Graph Regulated Nonnegative Matrix Factorization for Face Recognition. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-508845
Modern Language Association (MLA)
Yu, Zhe-Zhou…[et al.]. Incremental Graph Regulated Nonnegative Matrix Factorization for Face Recognition. Journal of Applied Mathematics No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-508845
American Medical Association (AMA)
Yu, Zhe-Zhou& Liu, Yu-Hao& Li, Bin& Pang, Shu-Chao& Jia, Cheng-Cheng. Incremental Graph Regulated Nonnegative Matrix Factorization for Face Recognition. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-508845
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-508845