A face image age recognition method based on an improved ensemble learning strategy

Abstract

A face image age recognition method based on an improved ensemble learning strategy comprises the following steps that (1) a plurality of weak classifiers need to be obtained in an ensemble learning model, each weak classifier can independently achieve prediction estimation on an input object, and a prediction model containing the weak classifiers is constructed; 2) a plurality of weak classifiersobtained based on the DCNN and a strong classifier obtained through integration all adopt softmax classifiers; 3) aan improved integrated learning strategy is adopted, firstly, following a combination method of a voting principle, and the credibility of each weak classifier'opinion ' is controlled by using a set threshold value T; Then, when the trust degree of the weak classifiers is generally low, a voting combination method is abandoned, and the confidence coefficient ai of each weak classifier is calculated to serve as the respective weight value; And finally, a probability distribution array of the strong classifier is obtained by using a weighted combination method, and a classification label corresponding to the maximum component of the strong classifier is taken as a final prediction result. . According to the invention, the accuracy is obviously improved;.

Description

technical field [0001] The invention relates to a face image age recognition method, in particular to a face image age recognition method based on an improved integrated learning strategy. Background technique [0002] With the rapid development of computer vision, pattern recognition and biometric technology, computer-based face age estimation has attracted more and more attention in recent years. It has a wide range of computer vision application prospects, including security detection, forensics, human-computer interaction (HCI), electronic customer information management (ECRM), etc. In real life, the use of surveillance cameras and age recognition systems can effectively prevent vending machines from selling cigarettes and illegal drugs to minors. In social security, fraud and illegal activities at ATMs usually occur in a specific age group, so it can be confirmed and prevented in advance by introducing age information. In the field of biometrics, facial age estimatio...

AI Technical Summary

Problems solved by technology

[0003] Although there are relevant studies on face age estimation at home and abroad, the estimation accuracy is not high due to the differences in individual age generation, the complexity of texture information, lack of data, and interference factors.

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