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Comparison of Transfer Learning Behaviour in Violence Detection with Different Public Datasets

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Abstract

The detection and recognition of violence have been area of interest to research, mainly in surveillance, Human-Computer Interaction and information retrieval for video based on content. The primary purpose of detecting and recognizing violence is to automatically and in real-time recognize violence. Hence, it is a crucial area and object of several studies, as it will enable systems to have the necessary means to contain violence automatically. In this sense, pre-trained models are used to solve general problems of recognition of violent activity. These models were pre-trained with datasets from: hockey fight; movies; violence in real surveillance; and fighting in real situations. From this pre-training models, general patterns are extracted that are very important to detect violent behaviour in videos. Our approach uses a state-of-the-art pre-trained violence detection model in general activity recognition tasks and then tweaks it for violence detection inside a car. For this, we created our dataset with videos inside the car to apply in this study.

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Acknowledgement

This work is supported by: European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039334; Funding Reference: POCI-01–0247-FEDER-039334].

Author information

Authors and Affiliations

  1. Centre Algoritmi, University of Minho, 4710-057, Braga, Portugal

    Dalila Durães, Flávio Santos, Francisco S. Marcondes & José Machado

  2. Bosch Car Multimedia, 4705-820, Braga, Portugal

    Sascha Lange

Authors
  1. Dalila Durães

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  2. Flávio Santos

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  3. Francisco S. Marcondes

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  4. Sascha Lange

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  5. José Machado

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Corresponding author

Correspondence toDalila Durães.

Editor information

Editors and Affiliations

  1. ISEP/GECAD, Polytechnic Institute of Porto, Porto, Portugal

    Goreti Marreiros

  2. IST/INESC-ID, University of Lisbon, Porto Salvo, Portugal

    Francisco S. Melo

  3. DETI/IEETA, University of Aveiro, Aveiro, Portugal

    Nuno Lau

  4. FEUP/LIACC, University of Porto, Porto, Portugal

    Henrique Lopes Cardoso

  5. FEUP/LIACC, University of Porto, Porto, Portugal

    Luís Paulo Reis

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Durães, D., Santos, F., Marcondes, F.S., Lange, S., Machado, J. (2021). Comparison of Transfer Learning Behaviour in Violence Detection with Different Public Datasets. In: Marreiros, G., Melo, F.S., Lau, N., Lopes Cardoso, H., Reis, L.P. (eds) Progress in Artificial Intelligence. EPIA 2021. Lecture Notes in Computer Science(), vol 12981. Springer, Cham. https://doi.org/10.1007/978-3-030-86230-5_23

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