A joint cascaded framework for simultaneous eye detection and eye state estimation
Gou, Chao1,3,4; Wu, Yue2; Wang, Kang2; Wang, Kunfeng1; Wang, Fei-Yue1,3; Ji, Qiang2
2017-07-01
发表期刊PATTERN RECOGNITION
卷号67期号:1页码:23-31
文章类型Article
摘要Eye detection and eye state (close/open) estimation are important for a wide range of applications, including iris recognition, visual interaction and driver fatigue detection. Current work typically performs eye detection first, followed by eye state estimation by a separate classifier. Such an approach fails to capture the interactions between eye location and its state. In this paper, we propose a method for simultaneous eye detection and eye state estimation. Based on a cascade regression framework, our method iteratively estimates the location of the eye and the probability of the eye being occluded by eyelid. At each iteration of cascaded regression, image features from the eye center as well as contextual image features from eyelid and eye corners are jointly used to estimate the eye position and openness probability. Using the eye openness probability, the most likely eye state can be estimated. Since it requires large number of facial images with labeled eye related landmarks, we propose to combine the real and synthetic images for training. It further improves the performance by utilizing this learning-by-synthesis method. Evaluations of our method on benchmark databases such as BioID and Gi4E database as well as on real world driving videos demonstrate its superior performance comparing to state-of-the-art methods for both eye detection and eye state estimation. (C) 2017 Elsevier Ltd. All rights reserved.
关键词Eye Detection Eye State Estimation Learning-by-synthesis Cascade Regression Framework
WOS标题词Science & Technology ; Technology
DOI10.1016/j.patcog.2017.01.023
关键词[WOS]PUPIL LOCALIZATION ; FEATURES ; ROBUST
收录类别SCI
语种英语
项目资助者University of Chinese Academy of Sciences (UCAS) ; UCAS ; RPI ; National Science Foundation(1145152) ; National Natural Science Foundation of China(61304200 ; 61533019)
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000399520700003
引用统计
被引频次:9[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/173211/14484
专题复杂系统管理与控制国家重点实验室_先进控制与自动化
通讯作者Gou, Chao
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Rensselaer Polytech Inst, Dept Elect Comp & Syst Engn, Troy, NY 12180 USA
3.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
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GB/T 7714
Gou, Chao,Wu, Yue,Wang, Kang,et al. A joint cascaded framework for simultaneous eye detection and eye state estimation[J]. PATTERN RECOGNITION,2017,67(1):23-31.
APA Gou, Chao,Wu, Yue,Wang, Kang,Wang, Kunfeng,Wang, Fei-Yue,&Ji, Qiang.(2017).A joint cascaded framework for simultaneous eye detection and eye state estimation.PATTERN RECOGNITION,67(1),23-31.
MLA Gou, Chao,et al."A joint cascaded framework for simultaneous eye detection and eye state estimation".PATTERN RECOGNITION 67.1(2017):23-31.
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