People tracking in video surveillance systems based on artificial intelligence

• Autorzy: Nasry Abir , Ezzahout Abderrahmane , Omary Fouzia

Identyfikatory

DOI

10.14313/JAMRIS/1‐2023/8

• Języki publikacji: EN

Abstrakty

EN

As security is one of the basic human needs, we need security systems that can prevent crimes from happen‐ ing. In general, surveillance videos are used to observe the environment and human behavior in a given location. However, surveillance videos can only be used to record images or videos, without additional information. There‐ fore, more advanced cameras are needed to obtain other additional information such as the position and move‐ ment of people. This research extracted this information from surveillance video footage using a person tracking, detection, and identification algorithm. The framework for these is based on deep learning algorithms, a popu‐ lar branch of artificial intelligence. In the field of video surveillance, person tracking is considered a challenging task. Many computer vision, machine learning, and deep learning techniques have been developed in recent years. The majority of these techniques are based on frontal view images or video sequences. In this work, we will compare some previous work related to the same topic.

Słowa kluczowe

EN

person tracking; person detection; person identification; video surveillance; artificial intelligence

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2023
• Tom: Vol. 17, No. 1
• Strony: 59--68
• Opis fizyczny: Bibliogr. 27 poz., rys.

Twórcy

autor

Nasry Abir

• Intelligent Processing and Security of System Team, Faculty of Science, Mohammed V University, Rabat, Morocco

• https://orcid.org/0000-0002-7144-0092

autor

Ezzahout Abderrahmane

• Intelligent Processing and Security of System Team, Faculty of Science, Mohammed V University, Rabat, Morocco

autor

Omary Fouzia

• Intelligent Processing and Security of System Team, Faculty of Science, Mohammed V University, Rabat, Morocco

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).