Advancements in Tactile Hand Gesture Recognition for Enhanced Human-Machine Interaction
由于人们对增强直觉性的人机交互（HRI/HVI）越来越感兴趣，本研究旨在提出一个稳健的触觉手势识别系统。我们对由导电纺织品构建的大型区域触觉感知界面（触摸界面）进行了全面的评估，以评估不同手势识别方法。我们的评估涵盖了传统特征工程方法以及能够实时解释各种手势的当代深度学习技术，包括适应手的大小、运动速度、施加压力水平和交互点的各种变化。我们对各种方法的深入分析在领域内的人机交互中做出了显著的贡献。
Motivated by the growing interest in enhancing intuitive physical Human-Machine Interaction (HRI/HVI), this study aims to propose a robust tactile hand gesture recognition system. We performed a comprehensive evaluation of different hand gesture recognition approaches for a large area tactile sensing interface (touch interface) constructed from conductive textiles. Our evaluation encompassed traditional feature engineering methods, as well as contemporary deep learning techniques capable of real-time interpretation of a range of hand gestures, accommodating variations in hand sizes, movement velocities, applied pressure levels, and interaction points. Our extensive analysis of the various methods makes a significant contribution to tactile-based gesture recognition in the field of human-machine interaction.
https://arxiv.org/abs/2405.17038
https://arxiv.org/pdf/2405.17038.pdf