A gaze gesture-based paradigm for situational impairments, accessibility, and rich interactions

Vijay Rajanna, T. Hammond
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引用次数: 7

Abstract

Gaze gesture-based interactions on a computer are promising, but the existing systems are limited by the number of supported gestures, recognition accuracy, need to remember the stroke order, lack of extensibility, and so on. We present a gaze gesture-based interaction framework where a user can design gestures and associate them to appropriate commands like minimize, maximize, scroll, and so on. This allows the user to interact with a wide range of applications using a common set of gestures. Furthermore, our gesture recognition algorithm is independent of the screen size, resolution, and the user can draw the gesture anywhere on the target application. Results from a user study involving seven participants showed that the system recognizes a set of nine gestures with an accuracy of 93% and a F-measure of 0.96. We envision, this framework can be leveraged in developing solutions for situational impairments, accessibility, and also for implementing rich a interaction paradigm.
基于注视手势的情境障碍、可访问性和丰富交互模式
计算机上基于注视手势的交互很有前景,但现有系统受到支持手势数量、识别准确性、需要记住笔画顺序、缺乏可扩展性等方面的限制。我们提出了一个基于注视手势的交互框架,用户可以在其中设计手势,并将它们与最小化、最大化、滚动等适当的命令相关联。这允许用户使用一组通用的手势与广泛的应用程序进行交互。此外,我们的手势识别算法与屏幕大小、分辨率无关,用户可以在目标应用程序的任何地方绘制手势。一项涉及7名参与者的用户研究结果显示,该系统识别9种手势的准确率为93%,f值为0.96。我们设想,这个框架可以用于开发针对情境障碍、可访问性以及实现富交互范式的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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