Journal of Computer Science and Technology

, Volume 19, Issue 5, pp 684–690 | Cite as

Unified model in identity subspace for face recognition

  • Pin LiaoEmail author
  • Li Shen
  • Yi-Qiang Chen
  • Shu-Chang Liu


Human faces have two important characteristics: (1) They are similar objects and the specific, variations of each face are similar to each other; (2) They are nearly bilateral symmetric. Exploiting the two important properties, we build a unified model in identity subspace (UMIS) as a novel technique for face recognition from only one example image per person. An identity subspace spanned by bilateral symmetric bases, which compactly encodes identity information. is presented. The unified model, trained on an obtained training set with multiple samples per class from a known people groupA, can be generalized well to facial images of unknown individuals, and can be used to recognize facial images from an unknown people groupB with only one sample per subject. Extensive experimental results on two public databases (the Yale database and the Bern database) and our own database (the ICT-JDL database) demonstrate that the UMIS approach is significantly effective and robust for face recognition.


pattern recognition face recognition identity subspace unified model 


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Copyright information

© Science Press, Beijing China and Allerton Press Inc., Beijing China and Allerton Press Inc. 2004

Authors and Affiliations

  • Pin Liao
    • 1
    Email author
  • Li Shen
    • 1
  • Yi-Qiang Chen
    • 1
  • Shu-Chang Liu
    • 2
  1. 1.Institute of Computing TechnologyThe Chinese Academy of SciencesBeijingP.R. China
  2. 2.Multimedia Information Technology Teaching Center, School of InformationBeijing University of Posts and TelecommunicationsBeijingP.R. China

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