The eye tracking field is an area highly studied by different researchers. In addition, there are companies that offer commercial eye trackers, but they are usually economically restrictive. However, current technology allows to design embedded eye tracking systems, capable of running on low-cost hardware. This paper presents the implementation of a real-time eye-detection method that uses the properties of “isophotes”, to achieve robustness against changes in illumination, eye rotation and pupil size. The method is implemented in a portable platform, reduced both in computing power and in RAM memory. The performance is evaluated using different eye tracking methods implemented by the authors on the same platform. For this purpose, a database generated on this hardware is used. This database is composed of a set of low-resolution near-infrared eyes-images created with the dark pupil technique, using a lightweight glasses head unit. Results show the robustness of the method and a significant accuracy improvement over the methods analyzed.

中文翻译：

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基于等光线的低计算功率眼检测嵌入式系统

眼动追踪领域是不同研究人员高度研究的领域。此外，还有一些公司提供商业眼动仪，但它们通常受到经济上的限制。然而，当前的技术允许设计能够在低成本硬件上运行的嵌入式眼动追踪系统。本文介绍了一种实时眼睛检测方法的实现，该方法使用“等光线”的属性，以实现对光照、眼睛旋转和瞳孔大小变化的鲁棒性。该方法在便携式平台中实现，降低了计算能力和 RAM 存储器。使用作者在同一平台上实施的不同眼动追踪方法来评估性能。为此，使用在该硬件上生成的数据库。该数据库由一组使用暗瞳技术创建的低分辨率近红外眼睛图像组成，使用轻型眼镜头单元。结果表明该方法的鲁棒性和对所分析方法的显着准确性改进。