ATK:基于3D手部追踪数据,在空中实现十指手写打字

Xin Yi, Chun Yu, M. Zhang, Sida Gao, Ke Sun, Yuanchun Shi
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引用次数: 89

摘要

十指徒手半空中打字是后桌面交互的潜在解决方案。然而,缺乏触觉反馈以及无法准确区分敲击手指或目标键是空中打字的主要挑战。在本文中,我们提出了ATK,一种新颖的交互技术,可以基于3D手部跟踪数据在空中进行徒手10指打字。我们的假设是,专业的打字员能够将他们的打字能力从物理键盘转移到空中打字。我们在设计ATK时采用了迭代方法。我们首先对用户的空中打字行为进行了实证调查,并研究了敲击过程中指尖的运动学、手指间的相关运动和敲击端点的三维分布。在此基础上,我们提出了一种概率敲击检测算法,并增强了Goodman的输入校正模型,以解决识别敲击手指的模糊性。我们最终通过一个4块研究来评估ATK的性能。参与者在第一个块中输入23.0个WPM,未纠正的词级错误率为0.3%,后来在最后一个块中达到29.2个WPM,而不牺牲准确性。
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ATK: Enabling Ten-Finger Freehand Typing in Air Based on 3D Hand Tracking Data
Ten-finger freehand mid-air typing is a potential solution for post-desktop interaction. However, the absence of tactile feedback as well as the inability to accurately distinguish tapping finger or target keys exists as the major challenge for mid-air typing. In this paper, we present ATK, a novel interaction technique that enables freehand ten-finger typing in the air based on 3D hand tracking data. Our hypothesis is that expert typists are able to transfer their typing ability from physical keyboards to mid-air typing. We followed an iterative approach in designing ATK. We first empirically investigated users' mid-air typing behavior, and examined fingertip kinematics during tapping, correlated movement among fingers and 3D distribution of tapping endpoints. Based on the findings, we proposed a probabilistic tap detection algorithm, and augmented Goodman's input correction model to account for the ambiguity in distinguishing tapping finger. We finally evaluated the performance of ATK with a 4-block study. Participants typed 23.0 WPM with an uncorrected word-level error rate of 0.3% in the first block, and later achieved 29.2 WPM in the last block without sacrificing accuracy.
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