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Automatic Fight Detection in Surveillance Videos

Authors:

Eugene Yujun Fu,

Stephen ChanAuthors Info & Claims

MoMM '16: Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media

Pages 225 - 234

https://doi.org/10.1145/3007120.3007129

Published: 28 November 2016 Publication History

Abstract

Affective computing is an up-surging research area relying on multimodal multimedia information processing techniques to study human interaction. Social signal processing under affective computing aims at recognizing and extracting useful human social interaction patterns. Fight is a common social interaction in real life. A fight detection system finds wide applications, such as in a prison, a bar and so on. Research works on fight detection are often based on visual features and demand substantive computation and good video quality. In this paper, we propose an approach to detect fights in a natural and low cost manner through motion analysis. Most existing works evaluated their algorithms on public datasets manifesting simulated fights, where the fight events are acted by actors. To evaluate on real fight scenarios, we collect fight videos from YouTube to form our own dataset. Based on the two types of datasets, we process the motion information to achieve fight detection. Experimental results indicate that our approach accurately detect fights in real scenarios. More importantly, we uncover some fundamental differences between real and simulated fights and could discriminate them well.

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Cited By

Gautam VMaheshwari HTiwari RAgarwal ATrivedi N(2024)Federated Learning Empowered Violence Recognition in CCTV Footage: A YOLO and ResNet-50 Fusion Approach2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)10.1109/IDCIoT59759.2024.10467832(01-06)Online publication date: 4-Jan-2024
https://doi.org/10.1109/IDCIoT59759.2024.10467832
Azimi SDe Sio CSterpone L(2023)Enhanced Video Surveillance Systems for “Signal for Help” Detection on Edge Devices2023 IEEE International Symposium on Technology and Society (ISTAS)10.1109/ISTAS57930.2023.10305989(1-4)Online publication date: 13-Sep-2023
https://doi.org/10.1109/ISTAS57930.2023.10305989
Sai Kiran PTirapathi Reddy BKeerthi GAvanigadda VVinnakota CSri D(2023)Violence Prediction System Using Bi-LSTM2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN)10.1109/ICPCSN58827.2023.00010(11-15)Online publication date: Jun-2023
https://doi.org/10.1109/ICPCSN58827.2023.00010
Show More Cited By

Index Terms

Automatic Fight Detection in Surveillance Videos
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding

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cover image ACM Other conferences

MoMM '16: Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media

November 2016

363 pages

ISBN:9781450348065

DOI:10.1145/3007120

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 28 November 2016

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Hong Kong Research Grant Council

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MoMM '16

MoMM '16: 14th International Conference on Advances in Mobile Computing and Multi Media

November 28 - 30, 2016

Singapore, Singapore

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Cited By

Gautam VMaheshwari HTiwari RAgarwal ATrivedi N(2024)Federated Learning Empowered Violence Recognition in CCTV Footage: A YOLO and ResNet-50 Fusion Approach2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)10.1109/IDCIoT59759.2024.10467832(01-06)Online publication date: 4-Jan-2024
https://doi.org/10.1109/IDCIoT59759.2024.10467832
Azimi SDe Sio CSterpone L(2023)Enhanced Video Surveillance Systems for “Signal for Help” Detection on Edge Devices2023 IEEE International Symposium on Technology and Society (ISTAS)10.1109/ISTAS57930.2023.10305989(1-4)Online publication date: 13-Sep-2023
https://doi.org/10.1109/ISTAS57930.2023.10305989
Sai Kiran PTirapathi Reddy BKeerthi GAvanigadda VVinnakota CSri D(2023)Violence Prediction System Using Bi-LSTM2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN)10.1109/ICPCSN58827.2023.00010(11-15)Online publication date: Jun-2023
https://doi.org/10.1109/ICPCSN58827.2023.00010
Paul AJain BSaranya G(2023)A Novel Framework for Potato Leaf Disease Detection Using Deep Learning Model2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10306654(1-6)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICCCNT56998.2023.10306654
Jain MBhanodia PSethi K(2023)Artificial Intelligent Model for Riot and Violence Detection that Largely Affect Societal Health and Local Healthcare SystemIndustry 4.0 and Healthcare10.1007/978-981-99-1949-9_6(113-131)Online publication date: 2-Dec-2023
https://doi.org/10.1007/978-981-99-1949-9_6
Sharma APathak JRajakumar P(2022)Disease Prediction using machine learning algorithms2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)10.1109/ICACITE53722.2022.9823744(995-999)Online publication date: 28-Apr-2022
https://doi.org/10.1109/ICACITE53722.2022.9823744
Bagga NSingh GBalusamy BShanker Singh A(2022)Violence Detection in Real Life Videos using Convolutional Neural Network2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)10.1109/ICACITE53722.2022.9823655(872-876)Online publication date: 28-Apr-2022
https://doi.org/10.1109/ICACITE53722.2022.9823655
Mumtaz NEjaz NHabib SMohsin STiwari PBand SKumar N(2022)An overview of violence detection techniques: current challenges and future directionsArtificial Intelligence Review10.1007/s10462-022-10285-356:5(4641-4666)Online publication date: 8-Oct-2022
https://doi.org/10.1007/s10462-022-10285-3
Eitta ABarabash TNafea YGomaa W(2021)Automatic Detection of Violence in Video Scenes2021 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN52387.2021.9533669(1-8)Online publication date: 2021
https://doi.org/10.1109/IJCNN52387.2021.9533669
Srivastava ABadal TGarg AVidyarthi ASingh R(2021)Recognizing human violent action using drone surveillance within real-time proximityJournal of Real-Time Image Processing10.1007/s11554-021-01171-2Online publication date: 12-Sep-2021
https://doi.org/10.1007/s11554-021-01171-2
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