Abstract
In this paper, a linear representation based face illumination normalization method is put forward. According to the Lambertian reflectance model, the specific illumination of a face image is determined linearly by a three-dimensional light source orientation vector. Based on the energy function proposed by the Quotient Image approach, we propose a two-step iterative optimization strategy to work out this three-dimensional face illumination representation coefficient vector. Then the neural illumination description coefficients learned from training set are transferred into each face image captured under arbitrary lighting condition to uniform face illumination. Our approach could effectively reduce the disturbance of varying illumination to recognition accuracy. The effectiveness of the proposed method is evaluated on the Extended Yale B database.
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Li, Y., Meng, L., Feng, J. (2012). Lighting Coefficients Transfer Based Face Illumination Normalization. In: Liu, CL., Zhang, C., Wang, L. (eds) Pattern Recognition. CCPR 2012. Communications in Computer and Information Science, vol 321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33506-8_34
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DOI: https://doi.org/10.1007/978-3-642-33506-8_34
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