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Method, device, equipment and storage medium for binocular living body recognition of the same face frame

A technology of the same face and face frame, applied in the computer field, can solve the problems of low accuracy and low security of binocular living body recognition, and achieve the effect of improving security and accuracy.

Active Publication Date: 2020-05-15
珠海亿智电子科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a method, device, equipment and storage medium for binocular living body recognition of the same face frame, aiming to solve the problem of low security caused by the low accuracy rate of binocular living body recognition in the prior art

Method used

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  • Method, device, equipment and storage medium for binocular living body recognition of the same face frame
  • Method, device, equipment and storage medium for binocular living body recognition of the same face frame
  • Method, device, equipment and storage medium for binocular living body recognition of the same face frame

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Experimental program
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Embodiment 1

[0037] figure 1 It shows the implementation flow of the method for recognizing the same human face frame provided by the binocular living body provided by the first embodiment of the present invention. For the convenience of explanation, only the parts related to the embodiment of the present invention are shown, and the details are as follows:

[0038] In step S101, the RGB image and the NIR image for binocular living body recognition are sampled to obtain a first face frame and a second face frame, the first face frame is a face frame in the RGB image, and the second face frame is obtained. The face frame is the face frame in the NIR image.

[0039] Embodiments of the present invention are suitable for binocular living body recognition equipment, which should have a first camera and a second camera, and the first camera is used to obtain RGB (R (red, red), G (green, green) , B (blue, blue), color mode) images, the second camera is used to acquire NIR (Near Infrared, near in...

Embodiment 2

[0051] figure 2 It shows the implementation flow of the training method of the face frame prediction model for binocular living body recognition of the same face frame provided by the second embodiment of the present invention. For the convenience of explanation, only the parts related to the embodiment of the present invention are shown, and the detailed description as follows:

[0052] S201: Obtain a working distance range for binocular living body recognition, and divide the working distance range into several equidistant distance scales.

[0053] In the embodiment of the present invention, the minimum working distance d of binocular living body recognition can be set according to the requirements of the application scene min , and the maximum working distance of binocular live recognition is d max , divide the working distance interval into n equal parts, and get n+1 distance scales

[0054] S202: In the overlapping area between the RGB image and the NIR image corres...

Embodiment 3

[0066] Figure 4 The structure of the device for binocular living body recognition of the same human face frame provided by Embodiment 3 of the present invention is shown. For the convenience of description, only the parts related to the embodiment of the present invention are shown, including:

[0067] Face frame acquisition unit 41, used to sample the RGB image and the NIR image of binocular living body recognition, obtain the first face frame and the second face frame, the first face frame is the face frame in the RGB image , the second face frame is a face frame in the NIR image;

[0068] The face frame prediction unit 42 is used to predict the third face frame corresponding to the first face frame by the trained face frame prediction model, and the third face frame is the face frame in the predicted NIR image ;as well as

[0069] A human face determination unit 43, configured to calculate the overlapping pixel area ratio of the third human face frame and the second huma...

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Abstract

The present invention is applicable to the field of computer technology, and provides a method, device, equipment and storage medium for confirming the same human face frame based on living body recognition, the method comprising: obtaining a first human face frame from an RGB image containing a human face frame identification , obtain the second face frame from the NIR image containing the face frame identification, the RGB image and the NIR image are taken by the same binocular camera, and the trained face frame prediction model predicts that the first face frame is in Corresponding to the corresponding third human face frame in the NIR image, calculate the overlapping pixel area ratio of the third human face frame and the second human face frame, when the overlapping pixel area ratio is greater than the preset area ratio threshold, determine the first The first human face frame and the second human face frame correspond to the same living human face, thereby improving the accuracy and recognition efficiency of human face living body recognition.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a method, device, equipment and storage medium for binocular living body recognition of the same human face frame. Background technique [0002] A very important application field of the binocular camera is the living body recognition in the face recognition system. In the binocular face recognition system, the face of the RGB image is used to compare with the registered face database to confirm whether it is a registered person. The face of the NIR image is used for live recognition to prevent various fake face attacks. When a non-registered person holds a face picture of a registered person close to his face, if the face position in the RGB image does not exactly match the face position in the NIR image, a The registered prosthetic RGB face and the attacker's NIR face are considered to be images of the same entity, thereby deceiving both the face recognition modu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
CPCG06V40/172G06V40/168G06V40/45
Inventor 不公告发明人
Owner 珠海亿智电子科技有限公司