The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2020.0111163
PDF

Moment Features based Violence Action Detection using Optical Flow

Author 1: A F M Saifuddin Saif
Author 2: Zainal Rasyid Mahayuddin

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 11, 2020.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Instantaneous detection of violence is still an unsolved research problem although artificial intelligence lives its prosperous years. The severity of injury causes due to violence can be minimized by detecting violence in real time demands for effective violence detection. Various methods were previously proposed for violence detection which could not provide robust results due many challenges, i.e. noise, motion estimation, lack of appropriate feature selection, lack of effective classification approach, complex background and variations in illumination. This research proposes an efficient method for violence detection using moment features to use motion patterns to facilitate detection in each frame and provides smaller area as region of interest. This means probability for extraction of motion intensity is getting lost because of same colored object in the background is reduced and thus minimizes background complexity. After that, proposed method uses optical flow to calculate angles and linear distances in each frame. In this context, if there is any frame loss due to noise or illumination variation, proposed method uses Kalman filter to process that frame by illuminating noise. Finally, decision for violence is determined using random forest classifier from single feature vector by generating a set of probabilities for each class. Proposed research performed extensive experimentation where accuracy rate of 99.12% was achieved using frame rate of 35 fps which is higher comparing with previous research results. Experimental results reveal the effectiveness of the proposed methodology.

Keywords: Violence detection; feature extraction; classification; optical flow

A F M Saifuddin Saif and Zainal Rasyid Mahayuddin, “Moment Features based Violence Action Detection using Optical Flow” International Journal of Advanced Computer Science and Applications(IJACSA), 11(11), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111163

@article{Saif2020,
title = {Moment Features based Violence Action Detection using Optical Flow},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111163},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111163},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {11},
author = {A F M Saifuddin Saif and Zainal Rasyid Mahayuddin}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Computer Vision Conference
  • Healthcare Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org