基于Faster R-CNN的人脸识别算法研究

Face recognition algorithm based on Faster R-CNN

人脸识别技术是身份认证的重要方式。旨在设计算法识别身份证人像与待检人像是否为同一旅客。使用卷积神经网络进行人脸识别算法的研究。使用检测人脸后计算人脸特征间距离的方式进行算法设计,最终达到95%的正确率。结果表明,FasterR-CNN算法能较精准的检测人脸,VGG-Net可以较好地提取人脸特征值,欧式距离可以精确计算人脸特征之间的距离。

Face recognition technology is an important way of identity authentication. The purpose of this paper was to design an algorithm to identify whether the identity witness and the person to be inspected were the same passengers. Face recognition algorithm based on convolutional neural network was studied. The algorithm was designed by calculating the distance between face features after face detection, and the final accuracy was 95%. The results show that Faster R-CNN algorithm can detect face accurately, VGG-Net can extract face feature values well, and Euclidean distance can accurately calculate the distance between face features.