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3D Face Feature Processing and Recognition Technology Cover
By: Hejing Wu  
Open Access
|May 2023

Figures & Tables

Figure 1.

Classification diagram
Classification diagram

Figure 2.

Network structure
Network structure

Figure 3.

Point structure
Point structure

Figure 4.

Traditional neural network diagram
Traditional neural network diagram

Figure 5.

Convolutional neural network diagram
Convolutional neural network diagram

Figure 6.

Flow chart of program execution
Flow chart of program execution

Figure 7.

Program execution result diagram
Program execution result diagram

Figure 8.

Facial recognition social program
Facial recognition social program

Figure 9.

“Patch” cracking Face ID
“Patch” cracking Face ID

Figure 10.

Campus access control system
Campus access control system

Description of returned values

FieldTypeInstructions
Request_idstringDistinguish each request, unique value
FacesAn array of stringThe array of faces that were detected
Image_idThe identification of the detected picture
Time_usedThe integerThe time taken for the entire request, in milliseconds.
Error_messagestringRequest failure information
Face_numThe integerThe number of faces recognized

Faces array values

FieldTypeInstructions
Face_tokenstringIdentification of human face
Face_rectangleobjectThe position of the face box contains the following attributes.Top: The ordinate of the upper left corner of the face boxleft: The abscissa of the upper left corner of the face boxwidth: The width of the face frameHeight: The height of the face frame
LandmarkobjectCoordinates of key points
AttributesobjectFacial feature information
Language: English
Page range: 9 - 20
Published on: May 26, 2023
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Hejing Wu, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.