基于肌电和陀螺仪的深度学习手部识别系统的应用

Chuan-Feng Chiu, T. Shih, Chi-Yen Lin, Lin Hui, Fitri Utaminingrum
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引用次数: 1

摘要

随着新技术的出现,人与计算机之间的互动变得越来越不可分割。人机交互(HCI)技术改善了人们生活中的操作,而手势识别是人机交互的基本操作,也是研究的热点之一。在本文中,我们开发了一个虚拟影院系统,使用手势来控制不同场景之间的变化,使用Myo臂章。该系统使用深度学习方法对动态手势进行分类,然后向虚拟剧院发送指令。通过使用该系统,用户可以方便地控制Unity开发的剧场场景和对象,使虚拟舞台在演出过程中更加丰富。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Hand Recognition System Based on Electromyography and Gyroscope Using Deep Learning
With the advent of new technological, the interaction between people and computers has become more and more inseparable. The human-computer interaction (HCI) technology improves the operations in people's lives, and the gesture recognition is the basic operation and is one of the hot research topics. In this paper, we developed a virtual theater system that using gesture to control the changes between different scene using the Myo armband. The proposed system used a deep learning method to classify dynamic gestures, and then send instructions to the virtual theater. By using this system, users can easily control the scenes and objects in the theater developed by Unity and make the virtual stage more enriched during the performance.
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