Face recognition method and system based on deep convolutional neural network

Abstract

The invention discloses a face recognition method and system based on a deep convolutional neural network. The method includes: detecting and cutting a step, receiving a photo of a face, obtaining the coordinates of key feature points of the face, and, based on preset cutting rules, according to The coordinates of the key feature points of the face determine the clipping boundary; the feature extraction step, based on the backbone network of the face depth recognition model, obtains the face feature vector of the fixed channel number according to the clipped picture; the identity recognition step matches the The face feature vector is used to obtain the identification information corresponding to the face feature vector according to the similarity; the age recognition step is to obtain the recognition age based on the age recognition model based on multiple age classifications according to the face feature vector. The invention can improve the recognition processing speed, improve the recognition accuracy of faces and ages, and save manpower and material resources by reusing face recognition models.

Description

technical field [0001] The invention relates to the technical field of face recognition, in particular to a face recognition method and system based on a deep convolutional neural network. Background technique [0002] Face recognition is a biometric technology for identification based on human facial feature information. With the maturity of its technology and the improvement of social recognition, face recognition is widely used in various fields. [0003] As a subsystem of face recognition, face age recognition usually puts age calculation on mobile devices. Considering the computing performance of its hardware, it adopts a non-deep learning mechanism with poor accuracy. At the same time, in specific applications, Age prediction usually waits for the face recognition results based on deep learning to return together, which will also increase the delay of the feedback results. Contents of the invention [0004] The present invention aims to solve at least one of the te...

AI Technical Summary

Problems solved by technology

[0003] As a subsystem of face recognition, face age recognition usually puts age calculation on mobile devices. Considering the computing performance of its hardware, it adopts a non-deep learning mechanism with poor accuracy. At the same time, in specific applications, Age prediction usually waits for the face recognition results based on deep learning to return together, which will also increase the delay of feedback results

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