Age classification assisted cross-age face recognition algorithm

Abstract

The invention relates to an age classification assisted cross-age face recognition algorithm. The algorithm comprises the steps of extracting and preprocessing a face image with an identity tag and an age tag; training an age classification assisted cross-age face recognition network, wherein the cross-age face recognition network comprises a convolutional network, an identity feature extraction network and an age feature extraction network; and inputting the preprocessed face image containing the identity tag and the age tag into the convolutional network, and outputting a shared feature by a final full connection layer of the convolutional network. The cross-age face recognition method has the beneficial effects that a cross-age face recognition deep learning model is improved, and age-invariant face features are extracted to improve the accuracy of cross-age face recognition; the Softmax loss function is used to ensure the inter-class difference of the features, and the Centor Loss loss function is introduced to reduce the intra-class difference of the face features, so that the boundaries of the feature vectors of different classes are clearer, and the feature vectors supplement each other and jointly participate in the updating of network parameters.

Description

technical field [0001] The invention belongs to the field of face recognition, and in particular relates to an age classification-assisted cross-age face recognition algorithm. Background technique [0002] With the continuous development of the society and the rapid improvement of the level of science and technology, a safe, reliable and portable identity authentication has become a common demand of the society. Compared with traditional identity authentication methods (such as password authentication, smart card authentication, dynamic password authentication, etc.), biometric technology provides higher security, more complex anti-counterfeiting and better portability. The so-called biometric identification technology is a technology that uses the inherent physiological characteristics of the human body (such as fingerprints, faces, irises, etc.) and behavioral characteristics (such as voice, handwriting, gait, etc.) to identify people's identities. The biological charact...

AI Technical Summary

Problems solved by technology

There are also some problems with this method. This data-driven method requires a relatively high-quality reference set, but the collection and organization of face image databases that change with age is precisely a major difficulty in cross-age face recognition.

Old age and early childhood images are missing more severely, while most age-labeled datasets have an almost uneven age distribution

Although with the development of the Internet, it is possible to collect pictures of various age groups, it is still a huge challenge to collect pictures of the same person from children to old age, which is a common problem of data-driven methods

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