基于CNN的人脸识别研究与实现  

Research and Implementation of Face Recognition Based on CNN

作　　者：谷广兵 沈晓萍[1] 王玉婷 GU Guangbing;SHEN Xiaoping;WANG Yuting(Jiaxing Vocational&Technical College,Jiaxing 314036,China)

机构地区：[1]嘉兴职业技术学院,浙江嘉兴314036

出　　处：《现代信息科技》2021年第13期14-17,22,共5页Modern Information Technology

摘　　要：人脸识别技术是人工智能一个典型的应用场景,为了实现基于微信小程序的人脸登录功能,文章对人脸区域检测、人脸特征提取、人脸判别内容进行了研究。人脸区域检测通过tensorflow-ssd进行模型搭建并采用widerface进行模型参数的训练。人脸特征提取采用facenet进行模型搭建并采用LFW数据集进行模型参数的训练,然后采用欧式距离进行人脸相似度计算,以TensorFlow将训练好的模型以PB格式存储,通过Python完成上述功能模块的封装,并与前端微信小程序完成数据交互。通过测试,系统可以完成人脸注册、人脸登录功能。Face recognition technology is a typical application scenario of artificial intelligence.In order to realize the face login function based on WeChat applet,the paper studies face region detection,face feature extraction and face discrimination.The face region detection model is built by tensorflow-ssd,and the model parameters are trained by wideface.Face feature extraction uses facenet to build the model and LFW data set to train the model parameters,then uses European distance to calculate the face similarity,stores the trained model in Pb format with tensorflow,completes the packaging of the above functional modules through python,and completes the data interaction with the front-end WeChat applet.Through the test,the system can complete the face registration and face login functions.

关 键 词：TensorFlow SSD facenet 人脸检测 人脸匹配 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]