Joint Estimation of Age and Expression by Combining Scattering and Convolutional Networks

被引:14
作者
Yang, Huei-Fang [1 ,3 ]
Lin, Bo-Yao [1 ,4 ]
Chang, Kuang-Yu [2 ]
Chen, Chu-Song [2 ]
机构
[1] Acad Sinica, Taipei, Taiwan
[2] Acad Sinica, Inst Informat Sci, Taipei, Taiwan
[3] Howard Hughes Med Inst, Janelia Res Campus, Ashburn, VA 20147 USA
[4] Univ Michigan, Elect & Comp Engn Dept, Ann Arbor, MI 48109 USA
关键词
Age estimation; deep learning; convolutional networks; expression recognition; multi-task learning; multi-level regression; scattering network; transfer learning; FACIAL EXPRESSIONS; RANK ESTIMATION; RECOGNITION; APPEARANCE; DATABASE;
D O I
10.1145/3152118
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article tackles the problem of joint estimation of human age and facial expression. This is an important yet challenging problem because expressions can alter face appearances in a similar manner to human aging. Different from previous approaches that deal with the two tasks independently, our approach trains a convolutional neural network (CNN) model that unifies ordinal regression and multi-class classification in a single framework. We demonstrate experimentally that our method performs more favorably against state-of-the-art approaches.
引用
收藏
页数:18
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