2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDARS-8.3
Paper Title VIOLENCE DETECTION FROM VIDEO UNDER 2D SPATIO-TEMPORAL REPRESENTATIONS
Authors Mohamed Chelali, Camille Kurtz, Nicole Vincent, Université de Paris, France
SessionARS-8: Image and Video Mid-Level Analysis
LocationArea I
Session Time:Monday, 20 September, 13:30 - 15:00
Presentation Time:Monday, 20 September, 13:30 - 15:00
Presentation Poster
Topic Image and Video Analysis, Synthesis, and Retrieval: Image & Video Mid-Level Analysis
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Action recognition in videos, especially for violence detection, is now a hot topic in computer vision. The interest of this task is related to the multiplication of videos from surveillance cameras or live television content producing complex 2D + t data. State-of-the-art methods rely on end-to-end learning from 3D neural network approaches that should be trained with a large amount of data to obtain discriminating features. To face these limitations, we present in this article a method to classify videos for violence recognition purpose, by using a classical 2D Convolutional Neural Network (CNN). The strategy of the method is two-fold: (1) we start by building several 2D spatio-temporal representations from an input video, (2) the new representations are considered to feed the CNN to the train/test process. The classification decision of the video is carried out by aggregating the individual decisions from its different 2D spatio-temporal representations. An experimental study on public datasets containing violent videos highlights the interest of the presented method.