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Can Haptic Feedback Improve Gesture Recognition in 3D Handwriting Systems?

机译:触觉反馈能否改善3D手写系统中的手势识别?

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Current gesture interfaces accept relatively simple postures and motions for reliable inputs, which are still far from natural and intuitive experiences for the users. This paper suggests a unique idea that haptic feedback has a potential to improve not only user experiences but also gesture recognition performances. We expect haptic feedback to provide users cues for natural writing movement and accordingly generate movement easily recognized by the system. We developed a writing gesture recognition system using the K-Means clustering algorithm for writing state estimation and a haptic feedback system which involved frictional sensation during writing and impulsive sensation at the beginning and ending of writing. The experiments on five participants showed an approximately 5% and 4% improvement in the true positive and the false negative gesture recognition rate with visual-haptic feedback compared to visual feedback alone. We confirmed that the improvement was due to changes in hand motion by haptic feedback, which led to a higher correlation between reference waveform and performed motion and an increase of the finger stopping time at the end of the writing. We also confirmed the positive effects of our haptic feedback on the user experiences.
机译:当前的手势界面接受相对简单的姿势和动作以进行可靠的输入,对于用户而言,这还远非自然而直观的体验。本文提出了一个独特的想法,即触觉反馈不仅可以改善用户体验,而且可以改善手势识别性能。我们期望触觉反馈能够为用户提供自然书写运动的线索,并因此产生易于被系统识别的运动。我们开发了一种使用K-Means聚类算法进行书写状态估计的书写手势识别系统,并开发了一种触觉反馈系统,该系统涉及书写过程中的摩擦感以及书写开始和结束时的冲动感。在五名参与者上进行的实验表明,与单独的视觉反馈相比,使用视觉触觉反馈的真实肯定和错误否定手势识别率分别提高了5%和4%。我们确认,这种改善是由于触觉反馈引起的手部动作变化所致,从而导致参考波形与所执行的动作之间的相关性更高,并且书写结束时手指停止时间的增加。我们还确认了触觉反馈对用户体验的积极影响。

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