计算机科学 ›› 2018, Vol. 45 ›› Issue (6): 284-290.doi: 10.11896/j.issn.1002-137X.2018.06.050
所属专题: 人脸识别
徐晓玲1,2, 金忠1,2, 贲圣兰3
XU Xiao-ling1,2, JIN Zhong1,2, BEN Sheng-lan3
摘要: 传统的最大间隔准则在计算类间离散度矩阵时往往忽略了类别之间的差异,但是对于人脸年龄估计,不同年龄标签之间的差异性是非常显著的。因此,在标签之间引入距离度量,提出标签敏感的最大间隔准则维数约减算法。此外,考虑到人脸变老的复杂性,提出两步的局部回归算法——K近邻-标签分布的支持向量回归(K Nearset Neighbors-Label Distribution Support Vector Reressor,KNN-LDSVR),以进行人脸年龄估计。在FGNET数据库子集上提出的人脸年龄估计方法的平均绝对误差为4.1岁,相对于已有的年龄估计方法,性能得到提升。
中图分类号:
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