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Vision-based Fight Detection from Surveillance Cameras by Aktı, Şeymanur; Tataroğlu, Gözde Ayşe; Ekenel, Hazım Kemal is a scholarly article available to read on EtoBox.

What is Vision-based Fight Detection from Surveillance Cameras about?

Vision-based action recognition is one of the most challenging research topics of computer vision and pattern recognition. A specific application of it, namely, detecting fights from surveillance cameras in public areas, prisons, etc., is desired to quickly get under control these violent incidents. This paper addresses this research problem and explores LSTM-based approaches to solve it. Moreover, the attention layer is also utilized. Besides, a new dataset is collected, which consists of fight scenes from surveillance camera videos available at YouTube. This dataset is made publicly available. From the extensive experiments conducted on Hockey Fight, Peliculas, and the newly collected fight datasets, it is observed that the proposed approach, which integrates Xception model, Bi-LSTM, and attention, improves the state-of-the-art accuracy for fight scene classification.

Author

Aktı, Şeymanur; Tataroğlu, Gözde Ayşe; Ekenel, Hazım Kemal

Published

2020

Language

EN