NDLI: Face illumination transfer through edge-preserving filters

Content Provider	IEEE Xplore Digital Library
Author	Xiaowu Chen Mengmeng Chen Xin Jin Qinping Zhao
Copyright Year	2011
Description	Author affiliation: State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, China (Xiaowu Chen; Mengmeng Chen; Xin Jin; Qinping Zhao)
Abstract	This article proposes a novel image-based method to transfer illumination from a reference face image to a target face image through edge-preserving filters. According to our method, only a single reference image, without any knowledge of the 3D geometry or material information of the target face, is needed. We first decompose the lightness layers of the reference and the target images into large-scale and detail layers through weighted least square (WLS) filter after face alignment. The large-scale layer of the reference image is filtered with the guidance of the target image. Adaptive parameter selection schemes for the edge-preserving filters is proposed in the above two filtering steps. The final relit result is obtained by replacing the large-scale layer of the target image with that of the reference image. We acquire convincing relit result on numerous target and reference face images with different lighting effects and genders. Comparisons with previous work show that our method is less affected by geometry differences and can preserve better the identification structure and skin color of the target face.
Starting Page	281
Ending Page	287
File Size	5318852
Page Count	7
File Format	PDF
ISBN	9781457703942
ISSN	10636919
e-ISBN	9781457703959
DOI	10.1109/CVPR.2011.5995473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face Image edge detection Lighting Kernel Image color analysis Smoothing methods Periodic structures
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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