It is the cache of ${baseHref}. It is a snapshot of the page. The current page could have changed in the meantime.
Tip: To quickly find your search term on this page, press Ctrl+F or ⌘-F (Mac) and use the find bar.

Application of Non-negative sparse matrix factorization in occluded face recognition | Lang | Journal of Computers
Journal of Computers, Vol 6, No 12 (2011), 2675-2679, Dec 2011
doi:10.4304/jcp.6.12.2675-2679

Application of Non-negative sparse matrix factorization in occluded face recognition

LiYing Lang, XueKe Jing

Abstract


In order to reduce the impact of block for the rate of face recognition ,in this paper, through the control of sparseness in the non-negative matrix factorization , the face image do non-negative sparse coding to obtain the eigenspace for the image. The experiment uses the ORL face database. The experimental results show that using NMFs obtains Eigenfaces with the local features of face and has a strong ability to express the occluded human face. The algorithm has good adaptability to partial occlusion, and has better robustness than PCA algorithm


Keywords


Face Recognition, Non-negative sparse matrix factorization, Feature Extraction; Proximal Support Vector Machine

References


[1] Guillamet D, Vitria J. Non-negative matrix factorization forface recognition, J. Lecture Notes on Artificial Intelligence,504(2):336-344,2002.

[2] Ouhsain M,Hamza A B.Image watermarking scheme us-ing nonnegative matrix factorization and wavelet transform.Expert Systems with Applications,36(2):2123-2129,2009.
http://dx.doi.org/10.1016/j.eswa.2007.12.046

[3] Guan X H,Wang W,Zhang X L.Fast intrusion detectionbased on a non-negative matrix factorization model. Journal of Network and Computer Applications,32(1):31-44,2009.
http://dx.doi.org/10.1016/j.jnca.2008.04.006

[4] Li Le and Zhang Yu-jin. A survey on algorithms of non-negative matrix factorization, J.Acta Electronica sinica,36(4):737-743,2008.

[5] Lee Ju-Hong,Park Sun, Ahna Chan-Min, and Kim Daeho.Automatic generic document summarization based on non-negative matrix factorization[J]. Information Processing and Management,6(2):20-34,2008.

[6] O H Patrik. Non negative Matrix Factorization with Sparseness Constraints, J.Journal of Machine Learning Research,(5):1457-1469,2004.

[7] Li L,Zhang Y J.Fast NMF:highly e-cient monotonic fixed-point non-negative matrix factorization algorithm with good applicability. Journal of Electronic Imaging,18(3):033004,2009.
http://dx.doi.org/10.1117/1.3184771

[8] Zhang Daoqiang, Zhou Zhi-Hua, Chen Songcan. Diagonalprincipal component analysis for face recognition,J. PatternRecognition,39(1):140-142,2006.

[9] LEE D D,SEUNG H S A lgorithms for non-negative matrix factorization,C.//Proc of Neural Information Processing Systems: 556-562,2000.

[10] Liu Y, Zhang H H, Park C, et al. Support vectormachineswith adap tive Lq penalty,J.Comput Statist and Data Anal, 51 (12) : 6380-6394, 2007.
http://dx.doi.org/10.1016/j.csda.2007.02.006


Full Text: PDF


Journal of Computers (JCP, ISSN 1796-203X)

Copyright @ 2006-2014 by ACADEMY PUBLISHER – All rights reserved.