Towards stabilizing facial landmark detection and tracking via hierarchical filtering: A new method

doi:10.1016/j.jfranklin.2019.12.043

	Towards stabilizing facial landmark detection and tracking via hierarchical filtering: A new method
	Jin, Yi 3; Guo, Xingyan 3; Li, Yidong 3; Xing, Junliang 2; Tian, Hui 1
刊名	JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
	2020-03-01
卷号	357 期号:5 页码:3019-3037
ISSN号	0016-0032
DOI	10.1016/j.jfranklin.2019.12.043
通讯作者	Li, Yidong(ydli@bjtu.edu.cn)
英文摘要	Many facial landmark detection and tracking methods suffer from instability problems that have a negative influence on real-world applications, such as facial animation, head pose estimation and real-time facial 3D reconstruction. The instability results of landmark tracking cause face pose shaking and face movement that is not fluent enough. However, most of the existing landmark detection and tracking methods only consider the stability of face location but neglect the stability of local landmark movement. To solve the problem of landmark local shaking, we present a novel hierarchical filtering method for stabilized facial landmark detection and tracking in video frames. The proposed method addresses the challenging landmark local shaking problem and provides effective remedies to solve them. The main contribution within our solution is a novel hierarchical filtering strategy, which guarantees the robustness of global whole facial shape tracking and the adaptivity of local facial parts tracking. The proposed solution does not depend on specific face detection and alignment algorithms, and thus, can be easily deployed into existing systems. Extensive experimental evaluations and analyses on benchmark datasets and 3D head pose datasets verify the effectiveness of our proposed stabilizing method. (c) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
资助项目	National Natural Science Foundation of China[61972030] ; National Natural Science Foundation of China[61672088] ; National Natural Science Foundation of China[KKA118001533]
WOS关键词	FACE ; MODEL
WOS研究方向	Automation & Control Systems ; Engineering ; Mathematics
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000527016400036
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/38833]
专题	智能系统与工程
通讯作者	Li, Yidong
作者单位	1.China Mobile Commun Corp, China Mobile Res Inst, Xuanwu Men West St, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 3.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
推荐引用方式 GB/T 7714	Jin, Yi,Guo, Xingyan,Li, Yidong,et al. Towards stabilizing facial landmark detection and tracking via hierarchical filtering: A new method[J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS,2020,357(5):3019-3037.
APA	Jin, Yi,Guo, Xingyan,Li, Yidong,Xing, Junliang,&Tian, Hui.(2020).Towards stabilizing facial landmark detection and tracking via hierarchical filtering: A new method.JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS,357(5),3019-3037.
MLA	Jin, Yi,et al."Towards stabilizing facial landmark detection and tracking via hierarchical filtering: A new method".JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 357.5(2020):3019-3037.