A Linear Reconstruction Method for Face Images under Normal Illumination
XIONG Peng-Fei1,2, LIU Chang-Ping1, HUANG Lei1
1.Character Recognition Engineering Center,Institute of Automation,Chinese Academy of Sciences, Beijing 100190 2.Graduate University of Chinese Academy of Sciences,Beijing 100049
Abstract Based on the stable relationships between the face representations under the certain and the normal illumination for different individuals, an approach to reconstruct face images under normal illumination is proposed. Firstly, to eliminate the impact of facial surfaces, an image deformation method in 3D domain is applied to achieve pixel-level alignment. Then, an illumination classification method based on image blocking is proposed to classify the images with the same lighting gradation. Finally, various linear reconstruction models of different illumination categories based on facial subspaces are trained from the preprocessing image pairs for face image reconstruction. The method effectively avoids the loss of the facial texture in image preprocessing and the distortion in image subspace. The experimental results of the proposed method on Extended Yale B demonstrate the performance in image representation and face recognition and verify the effectiveness in face alignment and illumination classification.
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2012, Vol. 25 
