Advanced Search
Volume 30 Issue 3
Dec.  2010
Turn off MathJax
Article Contents
Zhang Zhi-wei, Yang Fan, Xia Ke-wen, Yang Rui-xia . A Supervised LPP Algorithm and Its Application to Face Recognition[J]. Journal of Electronics & Information Technology, 2008, 30(3): 539-541. doi: 10.3724/SP.J.1146.2006.01258
Citation: Zhang Zhi-wei, Yang Fan, Xia Ke-wen, Yang Rui-xia . A Supervised LPP Algorithm and Its Application to Face Recognition[J]. Journal of Electronics & Information Technology, 2008, 30(3): 539-541. doi: 10.3724/SP.J.1146.2006.01258

A Supervised LPP Algorithm and Its Application to Face Recognition

doi: 10.3724/SP.J.1146.2006.01258 cstr: 32379.14.SP.J.1146.2006.01258
  • Received Date: 2006-08-28
  • Rev Recd Date: 2007-06-04
  • Publish Date: 2008-03-19
  • Illumination and pose variations make the performance of the Locality Preserving Projections (LPP)in face recognition decrease. To solve the problem, a supervised LPP using discriminant information is presented in this paper, the proposal calls for the establishment of a feature subspace in which the intrasubject variation is minimized, while the intersubject variation is maximized, then face recognition is implemented with the subspace. Experimentation results on Havard and Umist indicate that this approach is robust to illumination and pose and has higher recognition rate than LPP and other subspace methods.
  • loading
  • He X, Yan S, Hu Y, Niyogi P, and Zhang H J. Facerecognition using Laplacian faces[J].IEEE Trans. on PatternAnal. Machine Intelli.2005, 27(3):328-340[2]Turk M A and Pentland A P. Eigenfaces for recognition[J].Journal of Cognitive Neuroscience.1991, 3(1):71-86[3]Sam T, Roweis and Saul K L. Nonlinear dimensionalityreduction by locally linear embedding[J].Science.2000,290(5500):2323-2326[4]He X and Niyogi. Locality preserving projections.Proceedings of Advances In Neural Information ProcessingSystems 16, MA: Cambridge, MIT Press, 2004: 153-160.[5]Zhao Haitao, Sun Shaoyuan, Jing Zhongliang, and JingyuYang. Local structure based supervised feature extraction[J].Pattern Recognition.2006, 39(88):1546-1550[6]Roweis S, Saul L, and Hinton G. Global coordination of locallinear models. Proceedings of Advances in Neural InformationProcessing System 14, MA: Cambridge, MIT Press, 2001:889-896.[7]Hallinan P. A deformable model for face recognition underarbitrary lighting conditions. [PHD thesis]. Havard Univ,1995.[8]Graham D B and Allinson N M. Characterizing virtualeigensignatures for general purpose face recognition. In:Wechsler H., Phillips P.J., Bruce V., Fogelman-Soulie F.,Huang T.S. eds.. Face Recognition: From Theory toApplications. NATO ASI Series F, Computer and SystemsSciences, 1998, 163: 446-456.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (3867) PDF downloads(2000) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return