IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Artificial Intelligence in Video Surveillance

Artificial Intelligence in Video Surveillance
View Sample PDF
Author(s): Uma Maheswari P. (CEG, Anna University, Chennai, India), Karishma V. R. (Anna University, Chennai, India)and T. Vigneswaran (SRM-TRB Engineering College, India)
Copyright: 2023
Pages: 17
Source title: Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT
Source Author(s)/Editor(s): P. Swarnalatha (Department of Information Security, School of Computer Science and Engineering, Vellore Institute of Technology, India)and S. Prabu (Department Banking Technology, Pondicherry University, India)
DOI: 10.4018/978-1-6684-8098-4.ch001

Purchase

View Artificial Intelligence in Video Surveillance on the publisher's website for pricing and purchasing information.

Abstract

Surveillance is an essential component of security, and e-surveillance is one of the primary goals of the Indian Government's Digital India development initiative. Video surveillance offers a wide range of applications to reduce ecological and economic losses and becomes one of the most effective means of ensuring security. This chapter addresses the problem of how artificial intelligence is powering video surveillance. There is a significant research focus on video analytics but comparatively less effort has been taken for surveillance videos. However, there is little evidence that researchers have approached the issue of intelligent video surveillance in terms of suspicious action detection, crime scene description, face detection, crowd counting, and the like. Most AI-powered surveillance is based on deep neural networks and deep learning techniques using analysis of video frames as images. Consequently, this chapter aims to provide an overview and significance of how artificial intelligence techniques are employed in video surveillance and image processing.

Related Content

Fatima Ahmed Mohamed Abdalla, Noor Asiah Rashid. © 2026. 32 pages.
Fatima Ahmed Mohamed Abdalla, Noor Asiah Rashid. © 2026. 32 pages.
Azana Hafizah Mohd Aman, Wan Muhd Hazwan Azamuddin, Maznifah Salam, Zainab S. Attarbashi. © 2026. 32 pages.
Azana Hafizah Mohd Aman, Wan Muhd Hazwan Azamuddin, Maznifah Salam, Zainab S. Attarbashi. © 2026. 36 pages.
Salaheldin Mohamed Ibrahim Edam. © 2026. 42 pages.
Rubi Kadyan, Sunita Rani, Vinod Kr. Saroha. © 2026. 46 pages.
Mamoon M. Saeed, Zeinab E. Ahmed, Rania A. Mokhtar, Rashid A. Saeed. © 2026. 34 pages.
Body Bottom