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Face recognition model training and testing system and method based on multi-angle

A face recognition and model training technology, applied in the field of deep learning, can solve problems such as algorithm failure and effectiveness affecting classification speed and recognition performance

Active Publication Date: 2020-09-11
GOSUN GUARD SECURITY SERVICE TECH
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Problems solved by technology

Now commonly used feature extraction methods include principal component analysis (referred to as PCA algorithm), local binary pattern algorithm (referred to as LBP algorithm), etc., but these methods have limitations, usually for the feature extraction of frontal faces, but for non- For the feature extraction of frontal faces, these algorithms will fail, and the effectiveness of the face feature extraction model directly affects the speed of classification and recognition performance

Method used

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  • Face recognition model training and testing system and method based on multi-angle
  • Face recognition model training and testing system and method based on multi-angle
  • Face recognition model training and testing system and method based on multi-angle

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with accompanying drawing.

[0042] In this example, if figure 1 As shown, the multi-angle-based face recognition model training and testing system of the present invention includes four core modules in concrete implementation: a face sample database angle division module, a multi-angle training sample combination module, and a loss function calculation combined with face angles module, multi-angle face recognition model test module.

[0043] The angle division module of the face sample database first selects P pieces of continuous angle-changing photos of each face of N different people as a group of multi-angle photo sequences of faces, and rotates the face photos to be trained according to left-right rotation and up-down rotation The two direction angles are divided, the range of left and right rotation angles [-α, α] = [-75°, 75°], the range of up and down rotation angles [-β, β] = [-45°, 45°], ea...

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Abstract

The invention discloses a face recognition model training and testing system based on multi-angle, including a face sample database angle division module, a multi-angle sample combination training module, a loss function calculation module combined with face angles, and a multi-angle face recognition module. Model testing module. The invention is applicable to multi-angle human face recognition, can overcome the problem of poor recognition effect of non-frontal faces in the process of human face recognition, and improve the accuracy of non-frontal faces in the process of human face recognition.

Description

technical field [0001] The invention belongs to the field of deep learning for extracting facial features by a deep neural network, relates to technologies such as neural networks and pattern recognition, and in particular relates to multi-angle-based face recognition model training and testing methods. Background technique [0002] Face recognition technology is a research hotspot in artificial intelligence and pattern recognition today, and it is a biometric recognition method that automatically identifies people based on their facial features. It has a wide range of applications in access control, judicial applications, e-commerce and video surveillance and other fields. [0003] With the development of science and technology, the scope of application of face recognition has been continuously expanded, gradually extending from the field of public security criminal investigation to the civilian market, such as anti-theft doors with face recognition functions, face recognit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/161G06V40/172G06F18/2148
Inventor 章东平陶禹诺杨力张坤肖刚
Owner GOSUN GUARD SECURITY SERVICE TECH
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