A fully integrated violence detection system using CNN and LSTM

Author:

Sharma Sarthak,Sudharsan B.,Naraharisetti Saamaja,Trehan Vimarsh,Jayavel Kayalvizhi

Abstract

Recently, the number of violence-related cases in places such as remote roads, pathways, shopping malls, elevators, sports stadiums, and liquor shops, has increased drastically which are unfortunately discovered only after it’s too late. The aim is to create a complete system that can perform real-time video analysis which will help recognize the presence of any violent activities and notify the same to the concerned authority, such as the police department of the corresponding area. Using the deep learning networks CNN and LSTM along with a well-defined system architecture, we have achieved an efficient solution that can be used for real-time analysis of video footage so that the concerned authority can monitor the situation through a mobile application that can notify about an occurrence of a violent event immediately.

Publisher

Institute of Advanced Engineering and Science

Subject

Electrical and Electronic Engineering,General Computer Science

Cited by 7 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. A shallow 3D convolutional neural network for violence detection in videos;Egyptian Informatics Journal;2024-06

2. 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

3. Real Time Violence Detection Using Autonomous Intelligent Surveillance Robot;2023 2nd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA);2023-06-16

4. METHODS AND TECHNOLOGIES FOR INTELLECTUALIZATION OF SEARCHING FOR DESTRUCTIVE AND RADICAL CONTENT IN SOCIAL MEDIA: ANALYSIS OF THE CURRENT STATE;Vestnik komp'iuternykh i informatsionnykh tekhnologii;2023-04

5. 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

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