西安交通大学人工智能与机器人研究所,西安,710049
网络首发:2013-06-10,
纸质出版:2013
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刘剑毅, 何苗, 马瑶, 等. 面向人脸光照合成的光照参数精确估计算法[J]. 西安交通大学学报, 2013,47(6):18-24.
An Accurate Algorithm to Estiamte Illumination Parameter for Facial Relighting Synthesis[J]. 2013, 47(6): 18-24.
刘剑毅, 何苗, 马瑶, 等. 面向人脸光照合成的光照参数精确估计算法[J]. 西安交通大学学报, 2013,47(6):18-24. DOI: 10.7652/xjtuxb201306004.
An Accurate Algorithm to Estiamte Illumination Parameter for Facial Relighting Synthesis[J]. 2013, 47(6): 18-24. DOI: 10.7652/xjtuxb201306004.
为提高人脸图像光照合成的精度
提出了一种基于商图像的光照参数估计新算法。首先分析并指出传统商图像算法中存在恒定反射系数假设难以严格成立这一缺陷
它给光照参数估计引入了固有误差; 然后在参数化光照子空间框架下设计了一个改进的目标函数
用商图像本身去替代原算法中的反射系数比
从而弱化了假设条件的限制
允许人脸各像素点拥有独立的反射系数; 设计了一个迭代算法
通过线性系统来求解目标函数
能够实现对光照参数的高精度估计。在OFD人脸库和AI&R人脸库上的实验结果表明
所提光照参数估计算法具有良好的收敛性
光照参数估计精度的迹商指标可以获得25.49~43.09 dB的提升
光照合成图像中的峰值信噪比可以获得4.51~9.24 dB的提升。
A novel algorithm to estimate illumination parameter based on quotient image(QI)is proposed to improve the accuracy of facial image illumination synthesis. Analysis indicates that the hypothesis of uniform albedos in traditional QI algorithm can not be strictly hold
and that inherent error in illumination parameter estimation will be incurred. Then
an improved objective function is derived in the parametric illumination subspace framework
and the albedo ratios is replaced by the quotient image itself
so that the impacts of the hypothesis is weakened
and independent albedo per facial pixel can be permitted. An iterative algorithm is designed to solve the objective function through linear system
and illumination parameter can be estimated at high accuracy. Experiments on the oriental face database(OFD)and the AI&R face database show that the proposed algorithm has good convergence ability
and that the trace ratio for illumination estimation and the peak-signal-to-noise-ratio in illumination synthesis images are improved by 25.49~43.09 dB and 4.51~9.24 dB
respectively.
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西安交通大学. OFD东方人脸数据库. [DB/OL].(2007-04-08)[2012-08-19]. http:∥www.aiar.xjtu.edu.cn∥dfrlsjk5.html.
FU Raymondyun, ZHENG Nanning. M-Face: an appearance-based photorealistic model for multiple facial attributes rendering [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2006, 16(7): 830-842.
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