基于深度学习的手势识别系统的设计与实现

Design and Implementation of Gesture Recognition System Based on Deep Learning

针对无线投影系统市场需求量较大这一情况,文章设计一款基于深度学习的手势识别系统,采用ARM-A9开发板进行开发,通过摄像头获取用户手部图像数据,运用OpenCV机器视觉库进行图像处理,再使用tensorflow深度神经网络对处理后的图像进行模型训练,从而更好地识别用户的手势姿态,结合无线投影技术实现手势识别技术的进一步应用。

In view of the large market demand for wireless projection system,this paper designs a gesture recognition system based on deep learning,which is developed with ARM-A9 development board.The user’s hand image data is obtained through the camera,and the OpenCV machine vision library is used for image processing.Then the processed image is model trained with tensorflow deep neural network,so as to better recognize the user’s gesture,combined with wireless projection technology,the further application of gesture recognition technology is realized.