摘要
随着人工智能发展,过去的数年间,卷积神经网络,循环神经网络,自编码器,等领域发展迅速,但是由于移动设备的机能限制,很少存在移动设备上能够直接运行的网络模型,需要将网络轻量化才能在移动设备上使用。本文通过轻量化网络模型检测人体关键点,然后运用相关算法让人体动作和系统的指令相互匹配、反馈并形成一个完善的系统。
With the improvement of artificial intelligence,convolutional neural networks,cyclic neural networks,autoencoders,and other fields have developed rapidly in the past few years.However,due to the functional limitations of mobile devices,few models can run directly on mobile devices.The network model needs to be lightweight before it can be used on mobile devices.This paper uses lightweight network models to detect the key points of the human body,and then uses related algorithms to match human body movements and system commands,feedback and form a perfect system.
作者
范臻君
FAN Zhenjun(Renmin University of China,Beijing 100872,China)
出处
《现代信息科技》
2021年第14期86-89,共4页
Modern Information Technology
关键词
卷积神经网络
轻量级网络
人体检测
动作反馈
convolutional neural network
lightweight network
human body detection
action feedback
