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Eye/Head Tracking Technology to Improve HCI with iPad Applications

机译:眼/头跟踪技术可通过iPad应用改善HCI

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摘要

In order to improve human computer interaction (HCI) for people with special needs, this paper presents an alternative form of interaction, which uses the iPad's front camera and eye/head tracking technology. With this functional nature/capability operating in the background, the user can control already developed or new applications for the iPad by moving their eyes and/or head. There are many techniques, which are currently used to detect facial features, such as eyes or even the face itself. Open source bookstores exist for such purpose, such as OpenCV, which enable very reliable and accurate detection algorithms to be applied, such as Haar Cascade using very high-level programming. All processing is undertaken in real time, and it is therefore important to pay close attention to the use of limited resources (processing capacity) of devices, such as the iPad. The system was validated in tests involving 22 users of different ages and characteristics (people with dark and light-colored eyes and with/without glasses). These tests are performed to assess user/device interaction and to ascertain whether it works properly. The system obtained an accuracy of between 60% and 100% in the three test exercises taken into consideration. The results showed that the Haar Cascade had a significant effect by detecting faces in 100% of cases, unlike eyes and the pupil where interference (light and shade) evidenced less effectiveness. In addition to ascertaining the effectiveness of the system via these exercises, the demo application has also helped to show that user constraints need not affect the enjoyment and use of a particular type of technology. In short, the results obtained are encouraging and these systems may continue to be developed if extended and updated in the future.
机译:为了改善有特殊需要的人的人机交互(HCI),本文提出了一种替代形式的交互方式,该方式使用iPad的前置摄像头和眼/头跟踪技术。借助在后台运行的这种功能性质/功能,用户可以通过移动眼睛和/或头部来控制iPad的已开发或新应用程序。当前有许多技术可用于检测面部特征,例如眼睛甚至面部本身。出于这种目的,存在开源书店,例如OpenCV,它可以应用非常可靠和准确的检测算法,例如使用非常高级的编程的Haar Cascade。所有处理都是实时进行的,因此重要的是要密切注意iPad等设备的有限资源(处理能力)的使用。该系统在涉及22个不同年龄和特征的用户(戴着深色和浅色眼睛,戴着/不戴眼镜的人)的测试中得到了验证。执行这些测试以评估用户/设备的交互并确定其是否正常工作。在考虑了三个测试之后,系统获得了60%至100%的精度。结果表明,Haar级联在100%的情况下通过检测面部具有显着效果,这与眼睛和瞳孔的干扰(明暗)效果较差不同。除了通过这些练习确定系统的有效性之外,该演示应用程序还帮助表明用户约束不必影响特定类型技术的使用和使用。简而言之,获得的结果令人鼓舞,并且如果将来进行扩展和更新,则可以继续开发这些系统。

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