多层稀疏表达的人脸年龄估计  

Face Age Estimation Based on Multi-layer Spare Representation

作　　者：廖海斌 王电化 陈友斌[3] LIAO Haibin;WANG Dianhua;CHEN Youbin(School of Computer Science and Technology,Hubei University of Science and Technology,Xianning 437100,China;ZICT Technology Co.,Ltd,Shenzhen 518057,China;School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]湖北科技学院计算机科学与技术学院,湖北咸宁437100 [2]深圳中兴网信科技有限公司,广东深圳518057 [3]华中科技大学人工智能与自动化学院,湖北武汉430074

出　　处：《武汉大学学报（信息科学版）》2021年第8期1233-1240,共8页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金(61701174);咸宁市自然科学基金(2019kj130);湖北科技学院培育基金(2020-22GP03)。

摘　　要：人脸年龄分析是一个非常具有挑战性的工作:相对于其他的面部变化,人脸年龄变化不仅受内在因素(如基因)的影响,还受外在因素(如生活条件)的影响,很难找到准确刻画年龄变化的特征,因此,提出多层次稀疏表达的鲁棒性人脸年龄分析方法。该方法充分考虑人类对象识别的思维方式、相邻年龄相似性和信号稀疏表达分类原理,并融合主动表观模型、局部二元模式和仿生特征的各自特点。另外,为了降低人脸身份因子的干扰,提出了两因子分析方法进行人脸身份因子分离。实验结果表明,提出的方法具有很强的鉴别性和鲁棒性,在FG-NET和Morph2年龄库上平均绝对误差分别在4.65岁和3.64岁以内,证明了多层次稀疏表达的人脸年龄估计方法的有效性。Objectives:Face age estimation is still challenging because facial age image are not only affected intrinsic factors(e.g.genes),but also external factors(e.g.living conditions).Therefore,it is difficult to find features which can describe the variation of age accurately.Methods:We propose a robust face age analysis method based on multi-layer sparse representation,which combines the respective characteristics of active appearance model(AAM),local binary patterns(LBP)and bio-inspired features(BIF).This method will fully consider the way of object recognition of the human,the similarity of adjacent ages and the classifi-cation principle of signal sparse representation.In addition,in order to reduce the interference from the face identity factor,two-factors-analysis method is proposed to separate the face identity factor.Results:A large number of experiments are conducted on the public FG-NET,IFDB and MORPH2 datasets,and the mean absolute errors are within 4.65 years and 3.64 years for FG-NET and MORPH2 database,respectively.Conclusions:The experimental results show that the multi-layer sparse representation model has strong discrimination and robustness,which overcomes the shortcomings of traditional methods.

关 键 词：人脸年龄估计 人脸图像处理 特征提取 两因子分析 多层稀疏表达 

分 类 号：P237[天文地球—摄影测量与遥感] TP391[天文地球—测绘科学与技术]