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Application of AI-based real-time gesture recognition and embedded system in the design of english major teaching
Wireless Networks ( IF 2.1 ) Pub Date : 2021-07-19 , DOI: 10.1007/s11276-021-02693-0
Tian Zhang 1
Affiliation  

With the continuous development of science and technology, people have begun to interact with computer equipment, and human–computer interaction has become more and more simple. The human–computer interaction page is very user-friendly, people can communicate with the machine naturally, and can send signals through touch or gestures. In the process of person-to-person communication, gestures are a very common method that can convey specific signals. If you want to use gestures to send signals in human–computer interaction, you need to use the knowledge of computer vision to pave the way for human–computer interaction. We can deploy a teaching platform on the network platform to guide the teaching of English, which has become one of the teaching methods in many schools. In our school's research, we have incorporated some multimedia teaching in the English classroom teaching, and use multimedia teaching to stimulate students' interest in learning and improve their learning efficiency. We have changed the traditional teaching mode, through the way of human–computer interaction, using people's body movements and gesture information to interact. We also use AI technology to obtain the feature value of the vector angle through the three-dimensional characteristics of people's bones, and propose a KNN rapid recognition method. When constructing the English teaching system, we used the popular SSH framework and the C/S structure to design, and then we used design patterns to realize the reusability of the software. Finally, we conducted performance tests and functional tests on the system. The results show that this system can assist English teaching and can meet the needs of teaching.



中文翻译:

基于人工智能的实时手势识别与嵌入式系统在英语专业教学设计中的应用

随着科学技术的不断发展,人们开始与计算机设备进行交互,人机交互也变得越来越简单。人机交互页面非常人性化,人与机器自然交流,可以通过触摸或手势发送信号。在人与人的交流过程中,手势是一种很常见的方式,可以传达特定的信号。如果你想在人机交互中使用手势来发送信号,你需要利用计算机视觉的知识为人机交互铺平道路。我们可以在网络平台上部署教学平台来指导英语教学,这已经成为很多学校的教学方式之一。在我们学校的研究中,我们在英语课堂教学中加入了一些多媒体教学,利用多媒体教学来激发学生的学习兴趣,提高他们的学习效率。我们改变了传统的教学模式,通过人机交互的方式,利用人的身体动作和手势信息进行交互。我们还利用AI技术,通过人的骨骼三维特征获取矢量角度的特征值,提出了一种KNN快速识别方法。在构建英语教学系统时,我们采用流行的SSH框架和C/S结构进行设计,然后采用设计模式实现软件的可复用性。最后,我们对系统进行了性能测试和功能测试。

更新日期:2021-07-19
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