Real-Time Person Identification by Video Image Based on YOLOv2 and VGG 16 Networks

This paper deals with the problem of video-based face recognition. Nowadays, facial recognition methods have made a big step forward, but video-based recognition with its poor quality, difficult lighting conditions, and real-time requirements is still a difficult and unfinished task. The paper uses...

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Published in:Automation and remote control 2022-10, Vol.83 (10), p.1567-1575
Main Authors: Bobkov, A. V., Aung, Kh
Format: Article
Language:English
Subjects:
Algorithms
CAE) and Design
Calculus of Variations and Optimal Control
Optimization
Computer-Aided Engineering (CAD
Control
Face recognition
Mathematics
Mathematics and Statistics
Mechanical Engineering
Mechatronics
Real time
Robotics
Systems Theory
Thematic Issue
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Aung, Kh
description This paper deals with the problem of video-based face recognition. Nowadays, facial recognition methods have made a big step forward, but video-based recognition with its poor quality, difficult lighting conditions, and real-time requirements is still a difficult and unfinished task. The paper uses the apparatus of convolutional networks for various stages of processing: for capturing and detecting a face, for constructing a feature vector, and finally for recognition. All algorithms are implemented and studied in the Matlab environment to simplify their further export to embedded applications.
doi_str_mv 10.1134/S00051179220100095
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subjects Algorithms
CAE) and Design
Calculus of Variations and Optimal Control
Optimization
Computer-Aided Engineering (CAD
Control
Face recognition
Mathematics
Mathematics and Statistics
Mechanical Engineering
Mechatronics
Real time
Robotics
Systems Theory
Thematic Issue
title Real-Time Person Identification by Video Image Based on YOLOv2 and VGG 16 Networks
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