TR2004-025

Intra-Personal Kernel Space for Face Recognition


    •  Shaohua Zhou, Rama Chellappa, Baback Moghaddam, "Intra-Personal Kernel Space for Face Recognition", Tech. Rep. TR2004-025, Mitsubishi Electric Research Laboratories, Cambridge, MA, April 2004.
      BibTeX TR2004-025 PDF
      • @techreport{MERL_TR2004-025,
      • author = {Shaohua Zhou, Rama Chellappa, Baback Moghaddam},
      • title = {Intra-Personal Kernel Space for Face Recognition},
      • institution = {MERL - Mitsubishi Electric Research Laboratories},
      • address = {Cambridge, MA 02139},
      • number = {TR2004-025},
      • month = apr,
      • year = 2004,
      • url = {https://www.merl.com/publications/TR2004-025/}
      • }
  • Research Areas:

    Artificial Intelligence, Computer Vision, Machine Learning

Abstract:

Intra-personal space modeling proposed by Moghaddam et al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the intra-personal space using a principal component analysis and embedded in a probabilistic formulation. In this paper, we derived the principal subspace from the intra-personal kernel space by developing a probabilistic analysis of kernel principal components for face recognition. We test this new algorithm on a subset of the FERET database with illumination and facial expression variations. The recognition performance demonstrates its advantage over other traditional subspace approaches.