基于OpenCV的人脸图像识别系统设计与实现

Design and Implementation of Face Image Recognition System Based on OpenCV

基于轻量级的OpenCV软件库,提出了一种人脸表情图像识别系统。该系统结合了迁移学习策略和具有中心损失的联合监督方法,以优化人脸识别的过程。为了提高识别的准确性和速度,该系统采用MobileNet这一个轻量级的卷积神经网络模型,以实现脱机和实时框架中部署。为了验证该系统的有效性,分别使用两个常用的数据集对系统进行评估。实验结果显示,该系统能够提高人脸识别的准确度。

Based on the lightweight OpenCV software library,this paper proposes a facial expression image recognition system.The system combines a transfer learning strategy and a joint supervision method with center loss to optimize the process of face recognition.In order to improve the accuracy and speed of recognition,the system uses MobileNet,a lightweight convolutional neural network model,to implement offline and real-time deployment in the framework.In order to verify the effectiveness of the system,two commonly used data sets were used to evaluate the system.Experimental results show that the system can improve the accuracy of face recognition.