Robust Real-Time Violence Detection in Video Using CNN And LSTM

Robust Real-Time Violence Detection in Video Using CNN And LSTM
Author(s):
Reshma. S, Absa S.P, Riya S.R, Sreena V Wilson, Ms. R. Sajitha
Keywords:

Abstract
A major part of law enforcement and public safety is the detection of violent events in surveillance systems. The speed, accuracy, and adaptability of violence event detectors across a range of video sources in various forms provide measures for measuring their success. A number of studies focused on speed, accuracy, or both when detecting violence, but they ignored to account for adaptability across various types of video sources. In this paper, we suggested a deep-learning based real-time violence detector. CNN serves as a geometric feature extractor in the proposed framework, while LSTM is used as a time-based relation learning technique with a focus on the three factors (accuracy, speed, and overall flexibility). The advised model reached 98%.
Article Details
Unique Paper ID: 163048 Publication Volume & Issue: Volume 0, Issue no Page(s): 256 - 260
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org