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人类面部属性估计研究:综述
引用本文:曹猛,田青,马廷淮,陈松灿.人类面部属性估计研究:综述[J].软件学报,2019,30(7):2188-2207.
作者姓名:曹猛  田青  马廷淮  陈松灿
作者单位:南京信息工程大学 计算机与软件学院, 江苏 南京 210044,南京信息工程大学 计算机与软件学院, 江苏 南京 210044,南京信息工程大学 计算机与软件学院, 江苏 南京 210044,南京航空航天大学 计算机科学与技术学院, 江苏 南京 210016
基金项目:国家自然科学基金(61702273,61472186,61672281);江苏省自然科学基金(BK20170956);江苏省高校自然科学研究面上项目(17KJB520022)
摘    要:近年来,人脸属性估计因其广泛的应用而得到了大量的关注和研究,并且很多估计方法被提了出来.主要对现有相关工作进行归纳总结,为研究者提供相关参考.首先,根据是否考虑人脸性别、年龄、人种等不同属性间的内在关联,将现有的人脸面部属性研究方法划分成朴素的研究方法和自然的研究方法这两大类进行总结介绍.然后,从单一人脸数据库标记不完备、现有方法未能完备利用多属性联合估计、现有方法未能很好地利用各面部属性间关系这3个方面阐述当前方法的不足.最后,给出关于人脸面部属性估计进一步的研究方向.

关 键 词:面部属性估计  人脸面部估计  年龄估计  性别判别  人种识别  多属性联合估计
收稿时间:2018/8/8 0:00:00
修稿时间:2018/12/27 0:00:00

Human Facial Attributes Estimation: A Survey
CAO Meng,TIAN Qing,MA Ting-Huai and CHEN Song-Can.Human Facial Attributes Estimation: A Survey[J].Journal of Software,2019,30(7):2188-2207.
Authors:CAO Meng  TIAN Qing  MA Ting-Huai and CHEN Song-Can
Affiliation:School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China,School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China,School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China and College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Abstract:Over the past decades, human facial attributes (e.g. gender, age, and race) estimation has received large amount of attention and research due to its potential applications, and variety of methods have been proposed to address it. This article is devoted to review related works comprehensively and give references for researchers. Firstly, in accordance with whether exploiting the potential correlations between these facial attributes, the existing approaches are classified into naïve and natural groups and they are reviewed within each group. Then, in terms of incompleteness of annotated labels, considered attributes, and correlations utilization, the drawbacks of existing methods are analyzed. Finally, future research directions are provided at the end of this work.
Keywords:facial attributes estimation  human facial estimation  age estimation  gender recognition  race classification  multi-attributes joint estimation
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