Gazing point dependent eye gaze estimation. (November 2017)

• Record Type: Journal Article
• Authors: Cheng, Hong; Liu, Yaqi; Fu, Wenhao; Ji, Yanli; Yang, Lu; Zhao, Yang; Yang, Jie
• Is Part Of: Pattern recognition. Volume 71(2017:Nov.)
• Page Start: 36
• Page End: 44
• Publication Date: 2017-11
• Subjects: Eye gazing Tracking -- Virtual plane -- Cross-ratio -- Human Robot Interaction; Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2017.04.026
• Languages: English
• ISSNs: 0031-3203

Abstract

Highlights: A dynamic virtual plane projection, which is tangent to the cornea of pupil, is proposed to estimate the position of the gazing point. A two stage approach consisting of rough-to-precise framework for gazing point estimation is proposed. A heuristic strategy which contains off-line and on-line parameter learning for gazing point estimation is proposed. Abstract: 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°.