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信息技术21年13期

基于 CNN 的人脸识别研究与实现
谷广兵,沈晓萍,王玉婷
(嘉兴职业技术学院,浙江 嘉兴 314036)

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。


关键词:TensorFlow;SSD;facenet;人脸检测;人脸匹配



DOI:10.19850/j.cnki.2096-4706.2021.13.004


中图分类号:TP391.4                                     文献标识码:A                                   文章编号:2096-4706(2021)13-0014-05


Research and Implementation of Face Recognition Based on CNN

GU Guangbing, SHEN Xiaoping, WANG Yuting

(Jiaxing Vocational & Technical College, Jiaxing 314036, China)

Abstract: 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.

Keywords: TensorFlow; SSD; facenet; face detection; face matching


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作者简介:谷广兵(1986—),男,汉族,河南漯河人,讲师, 硕士,研究方向:计算机视觉、大数据技术、工业互联网。