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Face recognition model construction method, recognition method, equipment and storage medium

A face recognition and construction method technology, applied in the field of face recognition, can solve the problems of feature loss, face irregularity, local aliasing, etc., and achieve the effect of reducing the number of features and reducing memory consumption

Active Publication Date: 2019-12-13
CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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AI Technical Summary

Problems solved by technology

[0005] In real life, the occluder of the face is irregular, which is easy to cause problems such as feature loss, alignment error and local aliasing, which cannot be effectively processed by the traditional feature-based occluded face recognition method, resulting in the traditional The face recognition method is not as effective as deep learning in identifying occluded faces in an uncontrolled environment

Method used

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  • Face recognition model construction method, recognition method, equipment and storage medium
  • Face recognition model construction method, recognition method, equipment and storage medium
  • Face recognition model construction method, recognition method, equipment and storage medium

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Embodiment Construction

[0039] In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0040] Please refer to figure 1, which shows a flow chart of a face recognition model construction method provided by an embodiment of the present application, the method may include the following steps:

[0041] Step 11: Obtain an unoccluded face image.

[0042] Step 12: Preprocess the face image. The preprocessing methods include but are not limited to image size normalization, illumination normalization, and grayscale conversion according to the requirements of the deep learning network. For example, to prevent images in the face database from The pixel size is different, normalize the size of the picture, and then perform histogram equalization on the face image to normalize the illumination, and use opencv to directly read ...

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Abstract

The invention discloses a face recognition model construction method and device, a face recognition method and device and a storage medium. The method comprises steps of preprocessing face pictures, extracting four local areas, namely a left eye area, a right eye area, a nose area and a mouth area, of the preprocessed face image to perform face partitioning; amplifying the data on the basis of a partitioning result, respectively amplifying the data by considering the shielding of 1 / 2 and 1 / 4 conditions, and finally training a deep learning neural network by using the amplified data to construct a training feature data set, thereby realizing the face recognition based on feature matching. The method is good in shielded face recognition effect, does not need a large number of shielded samples, and is small in occupied memory.

Description

technical field [0001] The present application relates to the technical field of face recognition, and in particular to a face recognition model building method, recognition method, device and storage medium. Background technique [0002] Face recognition uses the existing face image database to authenticate unknown face images, which is an important biometric technology in the field of artificial intelligence and image information processing. Compared with the current mainstream biometric technologies such as fingerprint recognition, iris recognition, and voice recognition, face recognition has the advantages of non-invasiveness, good concealment, and high user acceptance, and the biological characteristics of the face are unique and difficult to be detected. Reproducibility. Therefore, face recognition technology is welcomed by all sectors of society and is widely used in various fields such as education, medical care, military, finance, justice, and factories. [0003] ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/04G06N3/08G06T7/11
CPCG06T7/11G06N3/08G06V40/161G06V40/171G06V40/172G06N3/045
Inventor 龙敏袁慧洁
Owner CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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