Human Violence Recognition in Video Surveillance in Real-Time

Herwin Alayn Huillcen Baca, Flor de Luz Palomino Valdivia, Ivan Soria Solis, Mario Aquino Cruz, Juan Carlos Gutierrez Caceres

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The automatic detection of human violence in video surveillance is an area of great attention due to its application in security, monitoring, and prevention systems. Detecting violence in real time could prevent criminal acts and even save lives. There are many investigations and proposals for the detection of violence in video surveillance; however, most of them focus on effectiveness and not on efficiency. They focus on overcoming the accuracy results of other proposals and not on their applicability in a real scenario and real-time. In this work, we propose an efficient model for recognizing human violence in real-time, based on deep learning, composed of two modules, a spatial attention module (SA) and a temporal attention module (TA). SA extracts spatial features and regions of interest by frame difference of two consecutive frames and morphological dilation. TA extracts temporal features by averaging all three RGB channels in a single channel to have three frames as input to a 2D CNN backbone. The proposal was evaluated in efficiency, accuracy, and real-time. The results showed that our work has the best efficiency compared to other proposals. Accuracy was very close to the result of the best proposal, and latency was very close to real-time. Therefore our model can be applied in real scenarios and in real-time.

Original languageEnglish
Title of host publicationAdvances in Information and Communication - Proceedings of the 2023 Future of Information and Communication Conference FICC
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages783-795
Number of pages13
ISBN (Print)9783031280726
DOIs
StatePublished - 2023
Event8th Future of Information and Computing Conference, FICC 2023 - Virtual, Online
Duration: 2 Mar 20233 Mar 2023

Publication series

NameLecture Notes in Networks and Systems
Volume652 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference8th Future of Information and Computing Conference, FICC 2023
CityVirtual, Online
Period2/03/233/03/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Channel average
  • Frame difference
  • Human violence recognition
  • Real scenario
  • Real-time
  • Video surveillance

Fingerprint

Dive into the research topics of 'Human Violence Recognition in Video Surveillance in Real-Time'. Together they form a unique fingerprint.

Cite this