Fast Face Detection in Violent Video Scenes

https://doi.org/10.1016/j.entcs.2016.12.002Get rights and content
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Abstract

In this work we aim to detect faces in violence scenes, in order to help the security control. We used the Violent Flow (ViF) descriptor with Horn-Schunck proposed in [V. Machaca Arceda and K. Fernańdez Fabián and J.C. Gutiérrez, Real Time Violence Detection in Video, “IET Conference Proceedings”, Institution of Engineering and Technology. (2016)] for violence scenes detection at first stage. Then we applied the non-adaptive interpolation super resolution algorithm to improve the video quality and finally we fire a Kanade-Lucas-Tomasi (KLT) face detector. In order to get a very low time processing, we paralleled the super resolution and face detector algorithms with CUDA. For the experiments we used the Boss Dataset and also we built a violence dataset, taking scenes from surveillance cameras. We have promising results detecting faces in this environment, because of the benefits of our proposal.

Keywords

ViF
Horn-Schunck
Optic Flow
Resolution enhancement
Video
Super-Resolution
Face detection
GPU parallel computing
Lower computational time

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