| Calibration Error Prediction: Ensuring High-Quality Mobile Eye-Tracking | |
| Li, Beibin1,2; Snider, J.C.3; Wang, Quan4; Mehta, Sachin5; Foster, Claire6; Barney, Erin3; Shapiro, Linda1; Ventola, Pamela7; Shic, Frederick3,8 | |
| 2022-06-08 | |
| 会议名称 | 2022 ACM Symposium on Eye Tracking Research and Applications, ETRA 2022 |
| 会议录名称 | Proceedings - ETRA 2022: ACM Symposium on Eye Tracking Research and Applications |
| 会议日期 | 2022-06-08 |
| 会议地点 | Virtual, Online, United states |
| 出版者 | Association for Computing Machinery |
| 产权排序 | 4 |
| 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. |
| 关键词 | datasets neural networks gaze detection text tagging |
| 作者部门 | 光谱成像技术研究室 |
| DOI | 10.1145/3517031.3529634 |
| 收录类别 | EI |
| ISBN号 | 9781450392525 |
| 语种 | 英语 |
| EI入藏号 | 20222612267177 |
| 引用统计 | |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/96027 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle; WA, United States 2.Microsoft Research, Redmond; WA, United States 3.Seattle Children's Research Institute, Seattle; WA, United States 4.Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China 5.Electrical and Computer Engineering, University of Washington, Seattle; WA, United States 6.Department of Psychology, Binghamton University, Binghamton; NY, United States 7.Yale Child Study Center, Yale University, New Haven; CT, United States 8.Department of Pediatrics, 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]:Association for Computing Machinery,2022. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Calibration Error Pr（529KB） | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 | ||
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