A review on video violence detection approaches | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 92، دوره 13، شماره 2، مهر 2022، صفحه 1117-1130 اصل مقاله (2.2 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6369 | ||
| نویسندگان | ||
| Mohamed Safaa Mohamed Shubber* ؛ Ziyad Tariq Mustafa Al-Ta'i | ||
| Department of Computer Science, College of Science, University of Diyala, Baqubah, Iraq | ||
| چکیده | ||
| A violent behaviour detection system (VBDS) is an important application of intelligent video surveillance that performs a critical role in the field of public security and safety VBDS is a sort of behaviour recognition that seeks to determine whether the behaviours observed in the situation are violent, such as fighting or assault. This paper presents a survey of the existing approaches to VBDS. In this paper, the existing VBDS techniques are classified based on their framework, which includes the old-fashion framework and the end-to-end state-of-the-art deep learning framework. Finally, the VBDS methods' performance is assessed and compared. | ||
| کلیدواژهها | ||
| Artificial intelligence؛ computer vision؛ Deep learning؛ Violent behaviour detection system (VBDS) | ||
| مراجع | ||
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