Letters: Adaptively weighted sub-pattern PCA for face recognition

Authors:
Keren Tan;Songcan Chen
Affiliations:
Department of Computer Science and Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing, 210016, China;Department of Computer Science and Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing, 210016, China
Venue:
Neurocomputing
Year:
2005

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Abstract

Adaptively weighted Sub-pattern PCA (Aw-SpPCA) for face recognition is presented in this paper. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub-patterns partitioned from an original whole pattern and separately extracts features from them. Moreover, unlike both SpPCA and mPCA that neglect different contributions made by different parts of the human face in face recognition, Aw-SpPCA can adaptively compute the contributions of each part and then endows them to a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on three standard face databases show that the proposed method is competitive.