Prof. Assoc. Dr. Adrian Leka1
1Faculty of Law, Luigj Gurakuqi University, Shkodra, Albania
MSc. Eraldi Ndoj2
2Faculty of Law, University of Tirana, Albania
Video has always been an essential element for law enforcement agencies in maintaining and promoting public safety. From local police to elite specialized units, law enforcement agencies around the world rely on video surveillance to gather operational information and evidence needed to maintain order, protect citizens and enhance security, whether within a neighborhood or at state borders.
Although law enforcement agencies rely heavily on video surveillance, it is not always the most practical method. First, it is difficult to watch live video recordings. Any person charged with this task would be prone to distraction and error. Critical details can be overlooked if they do not pay full attention to the Video Management System (VMS) or recordings. Even if the person is fully focused, it is easy to miss important objects that appear, especially if there is a lot of activity in the area being recorded.
Apart from live video viewing, video surveillance can also be used as supporting evidence in criminal investigations of incidents. Even this analysis does not escape from mistakes and lack of human attention, besides it takes a lot of time. Public and private spaces are monitored by multiple cameras, designed to cover every corner of the space. When records need to be checked, law enforcement agents must go through hours of records from several sources. Usually, it is impossible and ineffective to see all the records, so it is necessary to create a priority queue and set time limits for the completion of the work. Basically, it turns into a battle between the need to see all the evidence and the human resources needed for other investigations as well.
These needs of law enforcement agencies have given birth to Video Content Analytics (VCA). This paper will discuss how Video Content Analysis can be used to prevent crime and enable law enforcement and security agencies to overcome the challenges of video surveillance and utilize the full technological potential for productive video review and extracting predictive analytics from video content.
Volume 7. No.2 (2023): April – (Social Sciences Session)
ISSN 2661-2666 (Online) International Scientific Journal Monte (ISJM)
ISSN 2661-264X (Print)
DOI : 10.33807/monte.20232834
This is an open-access article under the CC BY-NC-ND license (creativecommons.org/licenses/by-nc-nd/4.0/)