Relative coordinates constraint for face alignment

doi:10.1016/j.neucom.2017.12.071

	Relative coordinates constraint for face alignment
	Nian, Fudong 1; Li, Teng 2; Bao, Bing-Kun 3; Xu, Changsheng4
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
	2020-06-28
卷号	395 页码:119-127
通讯作者	Bao, Bing-Kun(bingkunbao@njput.edu.cn)
摘要	We present a practical approach to improve the precision of face alignment for a single image. Recently, face alignment is deemed as a regression problem, and convolutional neural networks (CNNs) or recurrent neural networks (RNNs) are utilized to predict the coordinates of facial landmarks. However, most existing methods only adopt Euclidean loss as the optimization target for each landmark, and neglect the correlations between them, which we think may be inappropriate. To address this issue, in this paper, we introduce a novel Relative Coordinates Constraint (RCC) loss function for face alignment, which considers the relative coordinates between any pairs of landmarks as a new supervision signal. More importantly, we prove that the proposed RCC loss function is trainable and can be easily incorporated in existing CNNs optimization procedure. With the joint supervision of Euclidean loss and RCC loss, we train a robust and light CNNs framework for face alignment. Extensive experimental results on several datasets show that the precision of face alignment improved significantly by the proposed RCC loss and quantitative results are comparable to state-of-the-art methods (mean error 5.39 on 300-W and 6.99 on AFLW). In addition, the proposed framework is also an efficient solution (300 FPS on CPU). We share the implementation code of our proposed methods at https://github.com/nianfudong/RCC-loss. (C) 2019 Elsevier B.V. All rights reserved.
关键词	Face alignment Relative coordinates constraint CNN Loss function design
DOI	10.1016/j.neucom.2017.12.071
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61572503] ; National Natural Science Foundation of China[61572029] ; National Natural Science Foundation of China[61872424] ; National Natural Science Foundation of China[61930 00388] ; National Natural Science Foundation of China[6190070645] ; National Key R&D Program of China[2018YFB1305804] ; Scientific Research Development Foundation of Hefei University[19ZR15ZDA] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC039] ; NUPTSF[NY218001] ; Talent Research Foundation of Hefei University[16-17RC23] ; Talent Research Foundation of Hefei University[18-19RC54] ; Open fund for Discipline Construction, Institute of Physical Science and Information Technology, Anhui University
项目资助者	National Natural Science Foundation of China ; National Key R&D Program of China ; Scientific Research Development Foundation of Hefei University ; Key Research Program of Frontier Sciences, CAS ; NUPTSF ; Talent Research Foundation of Hefei University ; Open fund for Discipline Construction, Institute of Physical Science and Information Technology, Anhui University
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000536809600012
出版者	ELSEVIER
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/39565
专题	多模态人工智能系统全国重点实验室_多媒体计算
通讯作者	Bao, Bing-Kun
作者单位	1.Hefei Univ, Hefei, Peoples R China 2.Anhui Univ, Hefei, Peoples R China 3.Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing, Peoples R China 4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Nian, Fudong,Li, Teng,Bao, Bing-Kun,et al. Relative coordinates constraint for face alignment[J]. NEUROCOMPUTING,2020,395:119-127.
APA	Nian, Fudong,Li, Teng,Bao, Bing-Kun,&Xu, Changsheng.(2020).Relative coordinates constraint for face alignment.NEUROCOMPUTING,395,119-127.
MLA	Nian, Fudong,et al."Relative coordinates constraint for face alignment".NEUROCOMPUTING 395(2020):119-127.