Investigating LLE Eigenface on Pose and Face Identification

  • Shaoning Pang
  • Nikola Kasabov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


This paper introduces a new concept of LLE eigenface modelled by local linear embedding (LLE), and compares it with the traditional PCA eigenface from principle component analysis (PCA) on pose identity and face identity recognition through face classification. LLE eigenface is found outperforming PCA eigenface on the discrimination/recogntion of both face identity and pose identity. The superiority on face identity recognition is own to a more balanced energy distribution on LLE eigenfaces, while the superiority on pose identity recognition is due to the fact that LLE preserves a better local neighborhood of face images.


Face Recognition Face Image Independent Component Analysis Locally Linear Embedding Face Identity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shaoning Pang
    • 1
  • Nikola Kasabov
    • 1
  1. 1.Knowledge Engineering & Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand

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