Vision-based Fight Detection from Surveillance Cameras

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Authors Şeymanur Aktı, Hazım Kemal Ekenel, Gözde Ayşe Tataroğlu
Journal/Conference Name 2019 9th International Conference on Image Processing Theory, Tools and Applications, IPTA 2019
Paper Category
Paper Abstract 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.
Date of publication 2020
Code Programming Language Unspecified
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