Face recognition method and device, robot and storage medium

Abstract

The embodiment of the invention discloses a face recognition method and device, a robot and a storage medium. The face recognition method comprises the steps of obtaining a to-be-recognized face image; adopting a pre-trained face key point model to perform face key point recognition on the to-be-recognized face image, wherein the face key point model is a lightweight neural network model; aligningthe face image to be recognized according to the recognized face key points to obtain an aligned face image; extracting human face features in the aligned human face image; comparing the face featurewith a registered face feature in a preset database to recognize a person in the to-be-recognized face image, the registered face feature being obtained by performing feature extraction on a registered front face image; wherein the registered front face image is obtained by screening through a pre-trained face posture detection model. According to the method of the invention, the effect of accurately completing face recognition under the condition that the computing power of the equipment end is limited is achieved.

Description

technical field [0001] The present invention relates to the technical field of face recognition, in particular to a face recognition method, device, robot and storage medium. Background technique [0002] Face recognition is a biometric identification technology based on human facial feature information. With the rapid development of science and technology, face recognition technology is more and more applied to all walks of life, such as mobile phones, Security equipment and robots, etc. Based on this, the demand for technological innovation of face recognition technology is becoming more and more urgent. [0003] Face key point recognition is an important part of face recognition algorithms and applications. Among them, the accuracy of key point recognition will directly affect the accuracy of face recognition. To improve the accuracy of face key point recognition and the accuracy of subsequent face recognition, it is often necessary to set up a relatively complex networ...

AI Technical Summary

Problems solved by technology

To improve the accuracy of face key point recognition and the accuracy of subsequent face recognition, it is often necessary to set up a more complex network model.

[0004] Due to the limited computing power on the robot side, complex models are difficult to use on the robot side. Therefore, there is an urgent need for a face recognition method that can be used on the robot side

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