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Real-Time Human Detection for Intelligent Video Surveillance: An Empirical Research and In-depth Review of its Applications

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Abstract

A more efficient technique to guarantee safety and security in a variety of settings is through video surveillance, also known as closed circuit television (CCTV). It is frequently employed in strategic sectors, including security at home, public transportation, banks, and ATMs’ hubs, commercial districts, airports, and public roadways, and it is crucial for safeguarding crucial infrastructures. Due to the numerous uses, human detection in surveillance system video scenes has therefore grown in prominence in recent years. Objects of interest should be able to be found, categorized, and tracked by a real-time video surveillance system. This study provides an in-depth analysis of such video surveillance systems and presents a full assessment of methods and data sets utilized in human (object) detection. The most significant analyses of these systems are provided along with the employed architectures. To provide a clearer image and a comprehensive overview of the system, existing surveillance systems were compared in terms of their features, advantages, and challenges. These comparisons are summarized in this document. Future trends are also examined, laying the groundwork for new study avenues.

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Authors and Affiliations

  1. GSSS Institute of Engineering and Technology for Women, Affiliated to VTU Belagavi, Mysuru, Karnataka, India

    J. Usha Rani

  2. GSSS Institute of Engineering and Technology for Women, Mysuru, Karnataka, India

    P. Raviraj

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This article is part of the topical collection “Advances in Computational Intelligence for Artificial Intelligence, Machine Learning, Internet of Things and Data Analytics” guest edited by S. Meenakshi Sundaram, Young Lee, and Gururaj K. S.

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Usha Rani, J., Raviraj, P. Real-Time Human Detection for Intelligent Video Surveillance: An Empirical Research and In-depth Review of its Applications. SN COMPUT. SCI. 4, 258 (2023). https://doi.org/10.1007/s42979-022-01654-4

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