Recognition of Suspicious Human Activity in Video Surveillance: A Review
Received: 11 February 2023 | Revised: 21 February 2023 | Accepted: 25 February 2023 | Online: 18 March 2023
Corresponding author: Neha Gupta
Abstract
Over the past few years, there has been a noticeable growth in the use of video surveillance systems, frequently functioning as integrated systems that remotely monitor key locations. In order to prevent terrorism, theft, accidents, illegal parking, vandalism, fighting, chain snatching, and crime, human activities can be observed through visual surveillance in sensitive and public places like buses, trains, airports, banks, shopping centers, schools, and colleges. In this paper, a review of the state-of-the-art is provided, showing the overall development of identifying suspicious behavior from surveillance recordings over the past few years. We give a quick overview of the issues and difficulties associated with recognizing suspicious human activity. The purpose of this publication is to give this field's scholars a literature evaluation of several suspicious activity recognition systems along with their general structure.
Keywords:
suspicious activity, video surveillance, human activity, deep learningDownloads
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