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A Recent Review of Video Anomaly Detection for Smart Cities

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Advances on Intelligent Computing and Data Science (ICACIn 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 179))

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Abstract

According to Maslow’s hierarchy of needs, safety is a crucial component that must be satisfied before individuals can attend to higher up needs. Therefore, video surveillance systems have become more popular and heavily used in urban areas, expressing people's need for the safety of their lives and goods. However, video surveillance cameras alone cannot serve efficiently this purpose. Thusly, the urge for an automated video surveillance system has emerged to timely detect anomalies and raise early alarms to ensure public safety and security. In this paper, we will be focusing mainly on safety and security in smart cities, as we will be reviewing more precisely recent works related to video anomaly detection in public spaces, we will also provide the reader with a brief dataset benchmarking along with a comparative analysis of state-of-the-art literature.

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Author information

Authors and Affiliations

  1. Faculty of Science Ain Chock, University Hassan II, Casablanca, Morocco

    Marouane Ghoulami, Mounia Miyara, Najat Messaoudi & Zouhair Chiba

  2. Computer Science and Automation Department, EIGSICA, Casablanca, Morocco

    Hamza Toulni

  3. Faculty of Socio-Technical Systems Engineering, Vidzeme University of Applied Sciences, Valmiera, Latvia

    Mohcine Boudhane

Authors
  1. Marouane Ghoulami
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  2. Mounia Miyara
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  3. Najat Messaoudi
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  4. Zouhair Chiba
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  5. Hamza Toulni
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  6. Mohcine Boudhane
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Corresponding author

Correspondence to Marouane Ghoulami .

Editor information

Editors and Affiliations

  1. School of Computing and Digital Technology, Birmingham City University, Birmingham, UK

    Faisal Saeed

  2. Information Systems Department, School of Computing, Universiti Utara Malaysia (UUM), Sintok, Malaysia

    Fathey Mohammed

  3. Faculty of Sciences, University of Hassan II Casablanca, Casablanca, Morocco

    Errais Mohammed

  4. Department of Computing and Technology, Nottingham Trent University, Nottingham, UK

    Tawfik Al-Hadhrami

  5. College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

    Mohammed Al-Sarem

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Ghoulami, M., Miyara, M., Messaoudi, N., Chiba, Z., Toulni, H., Boudhane, M. (2023). A Recent Review of Video Anomaly Detection for Smart Cities. In: Saeed, F., Mohammed, F., Mohammed, E., Al-Hadhrami, T., Al-Sarem, M. (eds) Advances on Intelligent Computing and Data Science. ICACIn 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 179. Springer, Cham. https://doi.org/10.1007/978-3-031-36258-3_22

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