Fight Detection in Images Using Postural Analysis

  1. Eneko Atxa Landa 1
  2. José Gaviria de la Puerta 1
  3. Inigo Lopez-Gazpio 1
  4. Iker Pastor-López 1
  5. Alberto Tellaeche 1
  6. Pablo García Bringas 1
  1. 1 Universidad de Deusto
    info

    Universidad de Deusto

    Bilbao, España

    ROR https://ror.org/00ne6sr39

Libro:
Hybrid Artificial Intelligent Systems: 16th International Conference, HAIS 2021. Bilbao, Spain. September 22–24, 2021. Proceedings
  1. Hugo Sanjurjo González (coord.)
  2. Iker Pastor López (coord.)
  3. Pablo García Bringas (coord.)
  4. Héctor Quintián (coord.)
  5. Emilio Corchado (coord.)

Editorial: Springer International Publishing AG

ISBN: 978-3-030-86271-8,  978-3-030-86270-1

Año de publicación: 2021

Páginas: 231-242

Congreso: Hybrid Artificial Intelligent Systems (HAIS) (16. 2021. Bilbao)

Tipo: Aportación congreso

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Resumen

This paper defines the research process that has been carried out to develop a system for detecting fights in images. The system takes input frames and evaluates the probability that the frame contains one or more people fighting. Input frames containing images are initially processed using a well-known neural architecture, called Open-Pose, which extracts pose information out of images that contain human postures. Human posture data is then processed by heuristics to extract both: angles for arms and legs for each person in the image. Angles are then used to feed an additional neural network that has been trained to make probability predictions of people being potentially involved in fights. This paper describes the full pipeline regarding techniques, tools and assessment required to create a camera based violence detection system.

Fuente de los datos: Dialnet