Calibration Error Prediction: Ensuring High-Quality Mobile Eye-Tracking | |
Li, Beibin7,8; Snider, J.C.6; Wang, Quan5; Mehta, Sachin4; Foster, Claire3; Barney, Erin6; Shapiro, Linda8; Ventola, Pamela2; Shic, Frederick1,6 | |
2022-06-08 | |
会议日期 | 2022-06-08 |
会议地点 | Virtual, Online, United states |
关键词 | datasets neural networks gaze detection text tagging |
DOI | 10.1145/3517031.3529634 |
英文摘要 | Gaze calibration is common in traditional infrared oculographic eye tracking. However, it is not well studied in visible-light mobile/remote eye tracking. We developed a lightweight real-time gaze error estimator and analyzed calibration errors from two perspectives: facial feature-based and Monte Carlo-based. Both methods correlated with gaze estimation errors, but the Monte Carlo method associated more strongly. Facial feature associations with gaze error were interpretable, relating movements of the face to the visibility of the eye. We highlight the degradation of gaze estimation quality in a sample of children with autism spectrum disorder (as compared to typical adults), and note that calibration methods may improve Euclidean error by 10%.
© 2022 Owner/Author. |
产权排序 | 4 |
会议录 | Proceedings - ETRA 2022: ACM Symposium on Eye Tracking Research and Applications |
会议录出版者 | Association for Computing Machinery |
语种 | 英语 |
ISBN号 | 9781450392525 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/96027] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Department of Pediatrics, University of Washington, Seattle; WA, United States 2.Yale Child Study Center, Yale University, New Haven; CT, United States 3.Department of Psychology, Binghamton University, Binghamton; NY, United States 4.Electrical and Computer Engineering, University of Washington, Seattle; WA, United States 5.Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China 6.Seattle Children's Research Institute, Seattle; WA, United States 7.Microsoft Research, Redmond; WA, United States 8.Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle; WA, United States |
推荐引用方式 GB/T 7714 | Li, Beibin,Snider, J.C.,Wang, Quan,et al. Calibration Error Prediction: Ensuring High-Quality Mobile Eye-Tracking[C]. 见:. Virtual, Online, United states. 2022-06-08. |
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