Long-Range Gaze Tracking System for Large Movements
Long-Range Gaze Tracking System for Large Movements
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DOI：
10.1109/tbme.2013.2266413
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发表时间：
2013-12-01
影响因子：
4.6
通讯作者：
Kim, Whoi-Yul
中科院分区：
文献类型：
--
作者：
Cho, Dong-Chan;Kim, Whoi-Yul
在基于视觉的远程视线跟踪系统中，最具挑战性的课题是允许用户的自然运动以及增加系统的工作体积和距离。已经提出了几种考虑用户的自然运动的眼睛注视估计方法。但是，它们的工作体积和距离都很窄，很近。在本文中，我们提出了一种新的2-D映射为基础的视线估计方法，允许大运动的用户。传统的基于2-D映射的方法利用屏幕上的校准点与在用户校准步骤中获得的瞳孔中心角膜反射（PCCR）向量之间的映射函数。然而，PCCR矢量及其相关映射函数仅在执行用户校准的位置处或附近有效。所提出的运动映射函数，补充用户的运动，估计两个PCCR向量集之间的比例因子：一个在用户校准位置处获得，另一个在新的用户位置处获得。所提出的系统的目标是从1.4米到3米的较长范围的凝视跟踪。所提出的系统使用安装在平移和倾斜单元上的窄视角相机来捕获高分辨率的眼睛图像，提供约100 cm x 40 cm x 100 cm的宽而长的工作体积。实验结果表明，该方法成功地补偿了由于用户大幅度移动而导致的性能下降。平均角度误差为0.8度，当用户移动约81 cm时，角度误差仅增加0.07度。
In the vision-based remote gaze tracking systems, the most challenging topics are to allow natural movement of a user and to increase the working volume and distance of the system. Several eye gaze estimation methods considering the natural movement of a user have been proposed. However, their working volume and distance are narrow and close. In this paper, we propose a novel 2-D mapping-based gaze estimation method that allows large-movement of user. Conventional 2-D mapping-based methods utilize mapping function between calibration points on the screen and pupil center corneal reflection (PCCR) vectors obtained in user calibration step. However, PCCR vectors and their associated mapping function are only valid at or near to the position where the user calibration is performed. The proposed movement mapping function, complementing the user's movement, estimates scale factors between two PCCR vector sets: one obtained at the user calibration position and another obtained at the new user position. The proposed system targets a longer range gaze tracking which operates from 1.4 to 3 m. A narrow-view camera mounted on a pan and tilt unit is used by the proposed system to capture high-resolution eye image, providing a wide and long working volume of about 100 cm x 40 cm x 100 cm. The experimental results show that the proposed method successfully compensated the poor performance due to user's large movement. Average angular error was 0.8 degrees and only 0.07 degrees of angular error was increased while the user moved around 81 cm.