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TapSense: Enhancing Finger Interaction on Touch Surfaces

机译:TapSense:增强触摸表面上的手指交互

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摘要

We present TapSense, an enhancement to touch interaction that allows conventional surfaces to identify the type of object being used for input. This is achieved by segmenting and classifying sounds resulting from an object's impact. For example, the diverse anatomy of a human finger allows different parts to be recognized - including the tip, pad, nail and knuckle - without having to instrument the user. This opens several new and powerful interaction opportunities for touch input, especially in mobile devices, where input is extremely constrained. Our system can also identify different sets of passive tools. We conclude with a comprehensive investigation of classification accuracy and training implications. Results show our proof-of-concept system can support sets with four input types at around 95% accuracy. Small, but useful input sets of two (e.g., pen and finger discrimination) can operate in excess of 99% accuracy.
机译:我们介绍了TapSense,它是对触摸交互的增强,它允许常规表面识别用于输入的对象的类型。这是通过对对象撞击产生的声音进行分段和分类来实现的。例如,人类手指的多种解剖结构可以识别不同的部分-包括尖端,垫片,指甲和指关节-无需为用户提供器械。这为触摸输入打开了许多新的强大的交互机会,尤其是在输入受到极大限制的移动设备中。我们的系统还可以识别不同组的被动工具。我们以分类准确性和培训含义的全面调查作为结束。结果表明,我们的概念验证系统可以支持具有95%左右精度的四种输入类型的集合。小但有用的两个输入集(例如笔和手指的辨别)可以以超过99%的精度运行。

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