State-of-the-Art Violence Detection Techniques: A review

Author:

Biswas Milon,Jibon Afjal Hossain,Kabir Mim,Mohima Khandokar,Sinthy Rahman,Islam Md. Shamsul,Siddique Monowara

Abstract

Surveillance systems are playing a significant role in law enforcement and city safety. It is important to detect violent and suspicious behaviors automatically in video surveillance scenarios, for instance, railway stations, schools, hospitals to avoid any casualties which could cause social, economic, and ecological damage. Automatic detection of violence for quick actions is very significant and can efficiently help law enforcement departments. So, researchers are doing a lot of research on different techniques for detecting violence. This research study reviews various techniques and methods for detecting violent or anomalous activities from surveillance video that have been proposed by many researchers in recent years. The method of detection is divided into three categories. These categories are based on the classification techniques used. These categories are: traditional violence detection using machine learning, Support Vector Machine (SVM) & Deep Learning. Feature extraction & Object detection techniques are also described for each category. Moreover, dataset & video features that help in the recognition process are also discussed. The overall research finding has been discussed which will help the researcher in their future work in this field.

Publisher

Sciencedomain International

Subject

General Agricultural and Biological Sciences

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Real-time CCTV Footage Violence Detection with Alarm System using Deep Learning;2023 6th International Conference on Recent Trends in Advance Computing (ICRTAC);2023-12-14

2. An empirical study of various detection based techniques with divergent learning’s;Web Intelligence;2023-10-27

3. A hybrid learning frame work for recognition abnormal events intended from surveillance videos;Journal of Intelligent & Fuzzy Systems;2023-07-02

4. Violence Scene Detection from Social Media Networks Using Artificial Intelligence Methods;2023 International Conference on Information Technology, Applied Mathematics and Statistics (ICITAMS);2023-03-20

5. Violence Detection with Machine Learning: A Sociodemographic Approach;European Journal of Science and Technology;2023-01-07

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