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基于属性驱动损失函数的人脸识别算法

Face Recognition Algorithm Based on Attribute-Driven Loss Function

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摘要

为使通过卷积神经网络学习到的人脸识别特征更容易判别,在角度距离损失函数A-Softmax的基础上进行改进,将人脸属性融入到训练过程中,如性别、年龄和种族。使用属性驱动损失函数,利用属性邻近性对特征映射进行正则化,实验结果表明本方法学习到更多与属性相关的鉴别特征。本文改进算法在人脸验证数据集(包括LFW,CFP,AgeDB和 MegaFace)上均取得不错的效果,验证了该改进算法的有效性。

Abstract

To make the face recognition features learned from the convolutional neural network easier to identify, this paper improves the angular distance loss function A-Softmax by incorporating the facial attributes, such as gender, age, and race, into the training process. By using an attribute-driven loss function and regularizing the feature mapping with attribute proximity, the experimental result shows that more attribute-related discriminating features are learned by the proposed method. The improved algorithm has achieved good results in the face verification datasets, such as LFW, CFP, AgeDB, and MegaFace, verifying the effectiveness of the improved algorithm.

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补充资料

中图分类号:TP391.4

DOI:10.3788/LOP56.241505

所属栏目:机器视觉

基金项目:广州市科技计划;

收稿日期:2019-04-25

修改稿日期:2019-06-24

网络出版日期:2019-12-01

作者单位    点击查看

李燊:天津大学电气自动化与信息工程学院, 天津 300072
苏寒松:天津大学电气自动化与信息工程学院, 天津 300072
刘高华:天津大学电气自动化与信息工程学院, 天津 300072
吴慧华:天津大学电气自动化与信息工程学院, 天津 300072
王萌:天津大学电气自动化与信息工程学院, 天津 300072

联系人作者:刘高华(suppig@126.com)

备注:广州市科技计划;

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引用该论文

Li Shen,Su Hansong,Liu Gaohua,Wu Huihua,Wang Meng. Face Recognition Algorithm Based on Attribute-Driven Loss Function[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241505

李燊,苏寒松,刘高华,吴慧华,王萌. 基于属性驱动损失函数的人脸识别算法[J]. 激光与光电子学进展, 2019, 56(24): 241505

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