论文标题
$ pi_t $ - 使用虹膜功能运动向量增强眼睛跟踪的精度
$pi_t$- Enhancing the Precision of Eye Tracking using Iris Feature Motion Vectors
论文作者
论文摘要
最近通过跟踪虹膜功能的运动而不是利用学生边缘来证明了一种新的高精度眼睛追踪方法。尽管该方法提供了高精度，但它遭受时间漂移，无法跟踪眨眼以及在运动模糊存在下纹理匹配的损失。在这项工作中，我们提出了一种新的方法$ pi_t $，以最佳结合虹膜纹理和学生边缘的信息来解决这些问题。通过这种方法，我们在固定一系列小目标并遵循平稳移动的目标的同时，表现出至少48％和10％的精度（S2S-RMS和STD）的提高。此外，我们证明了鉴定距离为0.2度的目标之间微扫描的能力。
A new high-precision eye-tracking method has been demonstrated recently by tracking the motion of iris features rather than by exploiting pupil edges. While the method provides high precision, it suffers from temporal drift, an inability to track across blinks, and loss of texture matches in the presence of motion blur. In this work, we present a new methodology $pi_t$ to address these issues by optimally combining the information from both iris textures and pupil edges. With this method, we show an improvement in precision (S2S-RMS & STD) of at least 48% and 10% respectively while fixating a series of small targets and following a smoothly moving target. Further, we demonstrate the capability in the identification of microsaccades between targets separated by 0.2-degree.
