Shadow determination and compensation for face recognition

被引：0
|
作者：
Yi Li
Xiaodong Liu
Zhijun Gao
机构：
[1] Dalian University of Technology,School of Electronic and Information Engineering
[2] Heilongjiang University of Science and Technology,Department of Computer and Information Engineering
来源：
International Journal of Machine Learning and Cybernetics | 2014年 / 5卷
关键词：
Face recognition; Illumination variation; Shadow compensation; Robust PCA; Low-dimensional;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Illumination variation that occurs on face images will significantly influence the performance of the recognition. Based on the low-dimensional intrinsic of face images, we design a novel two-step shadow compensation method for face recognition. Three indexes are proposed and employed to distinguish the shaded-images. Then, we compensate the shadows adaptively by using a modified Robust PCA result. Experimental results on Yale database and Yale B database demonstrate that the proposed approach can improve the recognition rate. Showing our method is suitable for face recognition with illumination variations.
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页码：599 / 605
页数：6
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