Age assessment method based on face recognition technology

Abstract

An age assessment method based on face recognition technology is a method capable of considering affects on age estimation caused by race, sex, latitude (region), rural-urban difference. The method of using face recognition technology to estimate age has vast applicability and improves accuracy of age estimation observably. The method is based on an effective hypothesis, that is people with similar appearance has similar facial features at different ages, when estimating ages, just comparing the face image to be estimated with face image of different ages with higher appearance similarity, finding numbers of face images at different ages has highest appearance similarity with the object being estimated, proceeding weighted average to infer age of the object being estimated.

Description

technical field [0001] The invention is an age assessment method based on face recognition technology, which belongs to the technical field of image recognition and pattern recognition applications. Background technique [0002] In recent years, in the field of computer vision related to face image research, with the remarkable progress made in face detection and face recognition technology, people's research hotspots have gradually turned to more advanced methods such as facial expression analysis and age assessment. research topics. Among these topics, the application of age assessment in "providing different services for people of different age groups" has huge market potential. For example, a web browser with an age assessment function can determine whether a user is restricted from accessing some web pages, and a vending machine with an age assessment function can refuse to sell alcohol and tobacco to minors. [0003] The current usual age assessment method is to firs...

AI Technical Summary

Problems solved by technology

[0004] There are two key flaws in the current assessment method: first, it does not take into account the differences in facial features caused by factors such as race, gender, and living environment, which leads to the limitation of age assessment, that is, it can only guarantee the age of the assessed person. Higher accuracy is achieved when face images are consistent in terms of race, gender, etc.

The second is that even if the current technology collects a larger database for calculation, due to differences in race and living environment, the eigenvalues ​​​​of people of the same age group have huge differences, and effective eigenvectors cannot be established.

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