Cross-age face recognition method and system based on ternary constraints

A technology of face recognition and face recognition, which is applied in the field of cross-age face recognition methods and systems, and can solve problems affecting the performance of deep face recognition models, etc.

Pending Publication Date: 2021-11-26
南京英诺森软件科技有限公司
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AI Technical Summary

Problems solved by technology

[0003] In the existing technology, deep learning has been widely used in face recognition and has achieved very good performance. However, for cross-age face recognition problems, due to the difference between multiple faces of the same person at different ages There are very significant differences, which seriously affect the performance of existing deep face recognition models

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  • Cross-age face recognition method and system based on ternary constraints
  • Cross-age face recognition method and system based on ternary constraints
  • Cross-age face recognition method and system based on ternary constraints

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Embodiment

[0060] see Figure 1-2 , a cross-age face recognition method and system based on ternary constraints, comprising the following steps: 1. Acquiring face image samples with age-labeled information, wherein the above-mentioned samples can be crawled through public data sets and collected manually In practical applications, this step can obtain the original portrait data through a data acquisition device.

[0061] Step 2. Organize and train the collected data with age labels to obtain a face age attribute estimator.

[0062] Step 3. Perform age attribute estimation on a large batch of portrait data sets without age attribute information, and estimate approximate age attribute information. If the training data set itself has age attribute information, steps 1-2 can be ignored.

[0063] Step 4, the construction of the triple sample set, takes the sample set of each identity as the core, and divides the subsets of three time units of high, middle and low according to the age attribu...

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Abstract

The invention discloses a cross-age face recognition method and system based on ternary constraints, and belongs to the technical field of computer vision. According to the scheme, the method comprises steps of obtaining face sample data of different age spans, constructing an estimation model of age attributes, and estimating age attribute information for a training sample set, dividing three time units, respectively performing feature extraction on subsets of different age groups, taking the center features of different age groups of each identity object as a basis, continuously performing close constraint on the center features through features obtained by ternary sample set training, so that the feature aggregation effect of different age groups is improved, the final output result can be directly applied to a face recognition system. The features of different age groups are aggregated to obtain face features with finer granularity, and the problem that an existing face recognition method is low in recognition rate in cross-age-group face recognition can be effectively solved.

Description

technical field [0001] The present invention relates to the technical field of computer vision, and more specifically, to a method and system for cross-age face recognition based on ternary constraints. Background technique [0002] Face recognition is a biometric technology for identification based on human facial feature information. A camera or camera is used to collect images or video streams containing human faces, and automatically detect and track human faces in the images, and then detect A series of related technologies for facial recognition of the obtained face, usually also called portrait recognition, facial recognition, cross-age face recognition is a very challenging international problem in the field of face recognition, as we all know, the same person Pictures of different ages will have very large differences, and these differences will seriously affect the accuracy of cross-age face recognition. [0003] In the existing technology, deep learning has been ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06F18/23G06F18/214
Inventor 叶海亮
Owner 南京英诺森软件科技有限公司
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