Cross-age face recognition method based on online learning

A technology of age and face recognition, which is applied in the field of cross-age face recognition and face recognition. It can solve the problems of poor robustness of the age span of the face recognition algorithm, achieve high precision, reduce maintenance costs, and improve cross-age The effect of face recognition ability

Pending Publication Date: 2020-10-16
SOUTHEAST UNIV
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  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to address the deficiencies of the above-mentioned background technology, and to provide a cross-age face recognition method based on online learning, which improves the ability of cross-age fa...

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  • Cross-age face recognition method based on online learning
  • Cross-age face recognition method based on online learning
  • Cross-age face recognition method based on online learning

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Embodiment Construction

[0021] In order to more clearly illustrate the purpose, technical solution and technical effect of the present invention, the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0022] The present invention provides a cross-age face recognition method based on online learning, the model structure is as follows figure 1 As shown, including: face detection network, feature extraction network, age feature separation network. The identification method includes the following four steps.

[0023] Step 1. Train the feature extraction network. Use the face detection network MTCNN to perform face detection, alignment, and preprocessing on the image, and uniformly process the face image into a size of 112x112 pixels. The processed face image is input into the deep convolutional neural network for feature extraction, and the original feature vector of length K is obtained.

[0024] The ...

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Abstract

The invention discloses a cross-age face recognition method based on online learning, and belongs to the technical field of calculation, dead reckoning or counting. The method is realized by cascadinga model structure of an age feature separation network with a face feature extraction network. The face feature extraction network is trained on an external data set, so that the model has the capability of performing feature extraction on a face; the multi-task training of identity recognition and age prediction is performed on the age feature separation part by using the cross-age face data setto obtain an age-invariant face feature vector with higher robustness; in actual scene use, parameters of the feature separation part can be finely adjusted according to a newly input sample, and online learning of the neural network is realized. According to the method, the cross-age face recognition capability is improved to a certain extent while the model with low parameter quantity is used,online learning becomes possible due to the feature separation structure, and the model has the self-adaptive capability to a new scene.

Description

technical field [0001] The invention discloses a cross-age face recognition method based on online learning, relates to face recognition technology, and belongs to the technical field of calculation, calculation and counting. Background technique [0002] Face recognition is one of the most widely used and significant areas of computer vision tasks. Face recognition, as one of the biometrics, has the advantages of low cost, long-distance recognition, and no contact, compared with fingerprints, iris and other biometrics. In recent years, with the continuous development of deep learning, the face recognition algorithm based on deep convolutional neural network (Deep Convolutional Neural Network, DCNN) has shown a very powerful recognition ability, and the accuracy rate on the standard face verification data set LFW has reached Close to 100%. However, because age changes have a significant impact on facial features, general face recognition algorithms are generally not robust...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/16G06V40/161G06V40/172G06V40/168G06V40/178G06F18/22G06F18/214
Inventor 陆生礼缪烨昊庞伟
Owner SOUTHEAST UNIV
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