A review on video violence detection approaches

被引：3

作者：

Shubber, Mohamed Safaa Mohamed ^{[1
]}

Al-Ta'i, Ziyad Tariq Mustafa ^{[1
]}

机构：

[1] Univ Diyala, Coll Sci, Dept Comp Sci, Baqubah, Iraq

来源：

INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS | 2022年 / 13卷 / 02期

关键词：

Artificial intelligence; computer vision; Deep learning; Violent behavior detection system (VBDS);

D O I：

10.22075/ijnaa.2022.6369

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

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.

引用

页码：1117 / 1130

页数：14

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