With the increase in crime and terror rate globally, automated video surveillance, is the need of the hour. Surveillance along with the detection and tracking has become extremely important. Human detection and tracking is ideal, but the random nature of human movement makes it extremely difficult to track and classify as suspicious activities. The primary objective of this is to detect the suspiciously abandoned object recorded by the closed-circuit television cameras (CCTV). The main aim of this project is to ease the load on the controller at the main CCTV station by generating and alarm, whenever there is a detection of an abandoned object. To solve the problem, we first proceeded by the background subtraction such that we obtain the foreground image. Further, we calculated the inter-pixel distance and used area-based thresholding so as to differentiate between the person and the object. The object will further be tracked for a previously set time, which will help the system to decide whether or not the object is abandoned or not. Such a system that can ease the load on single CCTV controller can be deployed in places which require high discipline and security and are more prone to suspicious activities like Airports, Metro station, Railway Stations, entrances and exits of buildings, ATMs, and similar public places.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.