Violence Detection System using Convolution Neural Network

International Journal of Electronics and Communication Engineering
© 2019 by SSRG - IJECE Journal
Volume 6 Issue 2
Year of Publication : 2019
Authors : Goutham Sakthivinayagam, Raveena Easawarakumar, Alagappan Arunachalam and Dr. M. Pandi
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How to Cite?

Goutham Sakthivinayagam, Raveena Easawarakumar, Alagappan Arunachalam and Dr. M. Pandi, "Violence Detection System using Convolution Neural Network," SSRG International Journal of Electronics and Communication Engineering, vol. 6,  no. 2, pp. 5-8, 2019. Crossref, https://doi.org/10.14445/23488549/IJECE-V6I2P102

Abstract:

The demand for automatic action recognition systems has increased due to a rapid increase in the number of video surveillance cameras installed in cities and towns. The main purpose of the algorithm is used to generate an alarm in case of abnormal activities and to assist human operators and for offline inspection. A challenge is to develop intelligent video systems capable of automatically analyzing and detecting the violence that occurred in the scene. This work describes and evaluates the uses of Convolution neural networks to identify the violent content from video scenes. Also, it demonstrates the results and effectiveness of the proposed method when applied to our datasets. The result shows that the proposed system is more efficient and more accurate. This system helps the police to identify the criminals much faster. It may increase the chances of the criminals being caught.

Keywords:

Violence detection, Neural networks, Convolution neural networks, Crime, Video surveillance.

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