A Review on Physical Abuse Detection Techniques Using Video Surveillance Systems

Physical abuse is a significant societal issue with severe consequences for victims. The use of video surveillance systems has gained considerable attention as a potential tool for detecting and preventing physical abuse incidents. This review paper presents an in-depth analysis of the existing literature on physical abuse detection using video surveillance systems. The review begins by discussing the importance of physical abuse detection, applications, and the role of video surveillance systems in this context. It then explores different approaches used for physical abuse detection, including computer vision algorithms, machine learning techniques, and behavioral analysis methods, etc. The strengths and limitations of each approach are critically evaluated, highlighting their effectiveness in detecting physical abuse incidents. This paper also presents a comparative analysis of existing video surveillance systems designed specifically for physical abuse detection. It discusses their features, methodologies, accuracies, limitations, and deployment scenarios, allowing for a comprehensive understanding of contemporary technologies in this domain. By consolidating the existing knowledge and identifying research gaps, it aims to contribute to the development of more effective and ethically sound solutions to combat physical abuse.