BayesGaze: A Bayesian Approach to Eye-Gaze Based Target Selection.
BayesGaze: A Bayesian Approach to Eye-Gaze Based Target Selection.
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DOI：
10.20380/gi2021.35
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发表时间：
2021-05
期刊：
影响因子：
--
通讯作者：
Bi X
中科院分区：
文献类型：
--
作者：
Li Z;Zhao M;Wang Y;Rashidian S;Baig F;Liu R;Liu W;Beaudouin-Lafon M;Ellison B;Wang F;Ramakrishnan;Bi X
在本文中，准确，快速地选择目标的问题。然后选择目标的信号。通过分类分布建模的目标分布表明，贝叶斯湖可以改善基于居住的选择方法的目标选择准确性和速度，而重心映射中心（CM）。后部和合并先验可有效提高基于眼睛的目标选择的性能。
Selecting targets accurately and quickly with eye-gaze input remains an open research question. In this paper, we introduce BayesGaze, a Bayesian approach of determining the selected target given an eye-gaze trajectory. This approach views each sampling point in an eye-gaze trajectory as a signal for selecting a target. It then uses the Bayes’ theorem to calculate the posterior probability of selecting a target given a sampling point, and accumulates the posterior probabilities weighted by sampling interval to determine the selected target. The selection results are fed back to update the prior distribution of targets, which is modeled by a categorical distribution. Our investigation shows that BayesGaze improves target selection accuracy and speed over a dwell-based selection method, and the Center of Gravity Mapping (CM) method. Our research shows that both accumulating posterior and incorporating the prior are effective in improving the performance of eye-gaze based target selection.