计算机科学 ›› 2015, Vol. 42 ›› Issue (6): 32-36.doi: 10.11896/j.issn.1002-137X.2015.06.007
林时苗,毛晓蛟,杨育彬
LIN Shi-miao, MAO Xiao-jiao and YANG Yu-bin
摘要： 年龄是人固有的生物特征,随着年龄的变化,人脸特征也不断变化。近年来基于人脸图像的年龄估计方法的研究不断深入。基于人脸图像的年龄估计主要有两个阶段:特征提取和估计方法。针对以上两个阶段,分别提出相应的方法。在特征提取方面,为了更好地描述年龄变化,特别是针对未成年人,引入了方向梯度直方图(Histogram of Oriented Gradient,HOG)特征,并将其与局部二元模式(Local Binary Pattern,LBP)特征进行融合；在估计方法方面,提出了软双层估计模型, 其采用由粗到细的策略。首先,在第一层将人脸分成“未成年人”与“成年人”两类；然后,在第二层通过在两类的边界设置重叠区域,分别对其建立年龄估计模型,以对第一层的错误分类进行补救。通过实验发现,融合的特征具有更强的年龄判别性,同时,软双层模型也进一步提高了年龄估计的准确度。
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