Face recognition method and device based on dynamic threshold

Abstract

The invention provides a face recognition method and a device based on a dynamic threshold value. The method comprises a face recognition step, a cluster characteristic obtaining step, a category determining step and a judgment step, wherein the face recognition step is used for matching a face picture to be recognized with a preset formwork face picture to determine the formwork face picture with a highest similarity with the face picture to be recognized and determine a similarity score. The cluster characteristic obtaining step is used for respectively extracting scene characteristics of the face picture to be recognized and scene characteristics of the formwork face picture with the highest similarity with the face picture to be recognized and combining the similarity score to generate cluster characteristics. The category determining step is used for inputting the cluster characteristics to a preset scene category model to determine the scene category of the cluster characteristics. The judgment step is used for selecting the preset threshold value corresponding to the scene category, and judging the face recognition to be successful if the similarity score is larger than the threshold value. The problem of determining the threshold value is solved under the unrestraint scene, and at the same time, passing rate of the face recognition is enhanced.

Description

technical field [0001] The invention relates to the fields of computer image processing and pattern recognition, in particular to a face recognition method and device based on a dynamic threshold. Background technique [0002] As an effective technology for identification, face recognition technology has been developed rapidly and widely used in recent years. In the past few decades, face recognition has been widely used in commercial and law enforcement departments, such as criminal identification, credit card identification, security systems, on-site monitoring, access control and attendance, etc. [0003] With the promotion of practical applications, the problems and difficulties of face recognition have gradually become prominent. Changes in the application scene, such as changes in lighting, posture, and expression, may cause a person's variance in different environments to be greater than that of different people in the same environment. In addition, factors such as ...

AI Technical Summary

Problems solved by technology

The registration picture and the recognition picture will have a large difference in the recognition pass threshold under the same or different lighting environment, the same posture or different posture, the same expression or different expressions, so in the application of unconstrained scenes, the problem is : The pass threshold of face recognition should improve the face recognition pass rate in various application scenarios as much as possible while controlling misrecognition

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