Gazing point dependent eye gaze estimation

被引:28
|
作者
Cheng, Hong [1 ]
Liu, Yaqi [1 ]
Fu, Wenhao [1 ]
Ji, Yanli [1 ]
Yang, Lu [1 ]
Zhao, Yang [1 ]
Yang, Jie [2 ]
机构
[1] Univ Elect Sci & Technol China, Chengdu 611731, Sichuan, Peoples R China
[2] Carnegie Mellon Univ, Forbes Ave, Pittsburgh, PA 15213 USA
基金
中国国家自然科学基金;
关键词
Eye gazing Tracking; Virtual plane; Cross-ratio; Human Robot Interaction; TRACKING TECHNIQUES; CROSS-RATIO; CALIBRATION; APPEARANCE; POSITION; SYSTEM;
D O I
10.1016/j.patcog.2017.04.026
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cross-ratio invariant is used widely in projective transformations for eye gaze estimation. Establishing a virtual plane projection is an important step to use this property. Most of traditional cross-ratio approaches only used fixed parameters to calculate the gazing point. This paper proposes gazing point dependent eye gazing estimation approach. Our contributions are three-folded. First, we model a dynamic virtual plane projection, which is tangent to the cornea of pupil, to estimate the position of the gazing point. Second, we introduce a two stage approach consisting of rough-to-precise framework for gazing point estimation based on the gazing point dependent virtual plane projection. Third, a heuristic strategy which contains off-line and on-line parameter learning for gazing point estimation is proposed. The experiment results show that our approach can significantly improve the gazing estimation performance with an average accuracy of 0.70 degrees. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:36 / 44
页数:9
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