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
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