An Xception Model Based Real-time Violence Detection

A. Appavu, C. K. Babu
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Abstract

Nowadays the usage of CCTV surveillance is increasing. The number of cases of violence in public places like airports, railway stations, bus stops, shopping malls, restaurant, sports arenas and party halls have only been discovered after the fact. It is too late. Our objective be located to develop a complete structure capable of video analysis in real-time manner, which can identify the existence of violence from input video such as cctv and report the violence to concerned authorities such as higher authorities, police to take necessary action. In the proposed work using CNN for feature extraction and LSTM Interpreting features in chronological order. The distinct Xception system manner, we Achieving an effective solution for analysis video in real-time fashion through violent scenes obtained from the video allows us to legally monitor the situation with the relevant authorities. A mobile app, Telegram bot that can report the violent event Immediately to concern authorities.
基于异常模型的实时暴力检测
如今,闭路电视监控的使用越来越多。在机场、火车站、公交车站、商场、餐厅、运动场、聚会场所等公共场所发生的暴力事件是事后才发现的。太迟了。我们的目标是开发一个完整的结构,能够实时分析视频,从输入的视频(如cctv)中识别出暴力的存在,并向有关部门(如上级部门、警方)报告暴力事件,以采取必要的行动。在提出的工作中,使用CNN进行特征提取,LSTM按时间顺序解释特征。独特的例外系统方式,我们通过从视频中获取的暴力场景,实现了实时分析视频的有效解决方案,使我们能够合法地与相关部门进行监控。一款名为Telegram的移动应用程序可以立即向有关当局报告暴力事件。
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