• Maksym Ostapenko master Institute of Telecommunication Systems, Igor Sikorsky Kyiv Polytechnic Institute Kyiv, Ukraine,
  • Olena Shtogrina associate professor Institute of Telecommunication Systems, Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine,
  • Larysa Globa Prof DSc. in Computer Engineering, IEEE Professional Member, Chair of Information-telecommunication Networks, Institute of Telecommunication Systems, National Technical University of Ukraine "Igor Sikorsky Kiev Polytechnic Institute", Kyiv, Ukraine,
  • Andrii Astrakhantsev associate professor Institute of Telecommunication Systems, Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine,
  • Eduard Siemens professor Anhalt University of Applied Sciences, Future Internet Lab Anhalt, Köthen, Germany,



machine learning, video surveillance, re-identification, computer vision, deep learning


Background. The rapid growth of computational power of machines and amount of data caused exploding usage of computer vision in a large variety of tasks and in particular for people recognition.
Objective. The aim of the paper is to propose a computer vision re-identification system based on research. Also improvements for detection and recognition models of the system are made.
Methods. We used classical computer vision and deep learning techniques to create the system.
Results. The main contribution of the research is a description of the optimal system structure with a trade-of between speed and quality. Furthermore, requirements for an environment are proposed, which allows to set up the system in the real world with guaranteed quality.
Conclusions. Real-time computer vision re-identification system was developed and can be used in a production environment which satisfy requirements.


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