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

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Abstract

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.

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Authors and Affiliations

  1. Bauman Moscow State Technical University, Moscow, 105005, Russia

    A. V. Bobkov & Kh. Aung

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  1. A. V. Bobkov
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  2. Kh. Aung
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Correspondence to A. V. Bobkov or Kh. Aung.

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Translated by V. Potapchouck

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Bobkov, A.V., Aung, K. Real-Time Person Identification by Video Image Based on YOLOv2 and VGG 16 Networks. Autom Remote Control 83, 1567–1575 (2022). https://doi.org/10.1134/S00051179220100095

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