Towards stabilizing facial landmark detection and tracking via hierarchical filtering: A new method
文献类型：期刊论文
| 作者 | Jin, Yi1; Guo, Xingyan1; Li, Yidong1; Xing, Junliang2 ; Tian, Hui3
|
| 刊名 | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
 |
| 出版日期 | 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. |
| WOS关键词 | FACE ; MODEL |
| 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研究方向 | Automation & Control Systems ; Engineering ; Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000527016400036 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | National Natural Science Foundation of China |
| 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.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 3.China Mobile Commun Corp, China Mobile Res Inst, Xuanwu Men West St, Beijing, 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. |
入库方式： OAI收割
来源：自动化研究所
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