The use of a single uncalibrated camera is desirable for eye tracking to reduce the overall complexity and cost of the system. Quite often, at least one external light source is used to enhance image quality and generate a corneal reflection used as a reference point to estimate the point-of-gaze (PoG). Though the use of more than one light source has shown to enhance accuracy and robustness to head motion, it is unlikely that all corneal reflections appear in the eye images during natural eye movements. In this paper, we introduce the Screen-Light Decomposition (SLD) framework as a generalized model for PoG estimation using a single uncalibrated camera and a variable number of light sources. SLD synthesizes existing uncalibrated video-based eye trackers and can be used as a modeling tool to compare and design eye trackers. We have used the framework to design a novel eye-tracking technique, called SAGE, for single normalized space adaptive gaze estimation, that can gracefully degrade the gaze tracker performance when one or more corneal reflections are not detected, even during the calibration procedure. Results from an user experiment are presented to demonstrate its improved performance over other designs.

中文翻译：

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使用单个未校准相机和多个光源进行凝视点估计的屏幕光分解框架

期望使用单个未经校准的摄像机进行眼睛跟踪，以降低系统的整体复杂性和成本。通常，至少使用一个外部光源来增强图像质量并生成角膜反射，将其用作参考点以估计凝视点（PoG）。尽管已显示使用多个光源可以增强头部运动的准确性和鲁棒性，但在自然的眼球运动过程中，所有角膜反射都不太可能出现在眼图像中。在本文中，我们介绍了屏幕光分解（SLD）框架，它是使用单个未校准相机和可变数量的光源进行PoG估计的通用模型。SLD可以合成现有的未经校准的基于视频的眼动仪，并且可以用作建模工具来比较和设计眼动仪。我们已经使用该框架设计了一种称为SAGE的新颖眼动追踪技术，用于单归一化空间自适应注视估计，即使在校准过程中，即使未检测到一个或多个角膜反射，也可以优雅地降低注视跟踪器的性能。给出了用户实验的结果，以证明其相对于其他设计的改进性能。