Image-based face illumination transferring using logarithmic total variation models |
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Authors: | Qing Li Wotao Yin Zhigang Deng |
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Affiliation: | (1) Division of Computing Systems, School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore, Singapore, 639798;(2) Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong, China |
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Abstract: | In this paper, we present a novel image-based technique that transfers illumination from a source face image to a target face
image based on the Logarithmic Total Variation (LTV) model. Our method does not require any prior information regarding the
lighting conditions or the 3D geometries of the underlying faces. We first use a Radial Basis Functions (RBFs)-based deformation
technique to align key facial features of the reference 2D face with those of the target face. Then, we employ the LTV model
to factorize each of the two aligned face images to an illumination-dependent component and an illumination-invariant component.
Finally, illumination transferring is achieved by replacing the illumination-dependent component of the target face by that
of the reference face. We tested our technique on numerous grayscale and color face images from various face datasets including
the Yale face Database, as well as the application of illumination-preserved face coloring. |
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