Face age estimation method based on GAN extended multi-ethnic feature selection

A technology of race and face database, which is applied in the field of face age estimation, can solve the problem of restricting the age recognition of yellow, brown and other race pictures, and achieve the effect of improving recognition accuracy, enhancing processing functions, and improving accuracy

Active Publication Date: 2019-02-01
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

However, most of the research is based on existing data sets. Because there are too few samples of yellow, brown and other races

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  • Face age estimation method based on GAN extended multi-ethnic feature selection
  • Face age estimation method based on GAN extended multi-ethnic feature selection
  • Face age estimation method based on GAN extended multi-ethnic feature selection

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[0034] The present invention will be further described in detail below in conjunction with the accompanying drawings and examples. The following examples are explanations of the present invention and the present invention is not limited to the following examples.

[0035] The Generative Adversarial Network (GAN) is composed of a generative model G and a discriminative model D, which trains datasets and generates new data samples through confrontational learning. In 2014, Goodfellow published the article "Generative Adversarial Networks", which made the generative adversarial network debut in academia. Its main idea comes from game theory (that is, the sum of the interests of two people is zero, and the gain of one party is the loss of the other). Since then, GAN has been applied to solve various practical problems, such as language, speech processing, and chess and card game programs. The generation model G captures the distribution of the sample data, and generates a sample s...

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Abstract

The invention discloses a method for estimating human face age based on GAN extended multi-race feature cooperative selection. Firstly, simulating generation of multi-style human face samples is carried out through a generating antagonism network, so as to rapidly and large-scale expand human face databases of different races, thereby improving the recognition accuracy of age information of yellow, brown and other races. Then the convolution neural network is used to pre-train the original dataset, and then further refined training is carried out based on the expanded face age database. And finally four people of Sub-CNN performs joint feature selection fusion based on group sparse algorithm to solve the problem of age estimation based on face image. The invention obtains a face age estimation model with more generalization ability, and at the same time, the invention can greatly improve the performance of a face recognition system of many ages, and makes up for the shortcomings of theprevious research.

Description

technical field [0001] The invention relates to a method for estimating the age of a human face, in particular to a method for estimating the age of a human face based on collaborative selection of multi-ethnic characteristics based on GAN expansion. Background technique [0002] With the rapid development of related theories and applications of human-computer interaction, age information, as an important biological characteristic of human beings, has many application requirements in this field and has an important impact on the performance of face recognition systems. However, most of the research is based on existing data sets. Because there are too few samples of yellow, brown and other races in many existing large data sets abroad, the age recognition of yellow, brown and other race pictures is greatly limited. Contents of the invention [0003] The technical problem to be solved by the present invention is to provide a face age estimation method based on GAN extended ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/16G06V40/168G06V40/178G06F18/214
Inventor 田青沈传奇毛军翔孙元康秦璇黄媛沅
Owner NANJING UNIV OF INFORMATION SCI & TECH
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