  In this paper of a research based project, using Bidirectional Long
Short-Term Memory (BiLSTM) networks, we provide a novel Fight Scene Detection
(FSD) model which can be used for Movie Highlight Generation Systems (MHGS)
based on deep learning and Neural Networks . Movies usually have Fight Scenes
to keep the audience amazed. For trailer generation, or any other application
of Highlight generation, it is very tidious to first identify all such scenes
manually and then compile them to generate a highlight serving the purpose. Our
proposed FSD system utilises temporal characteristics of the movie scenes and
thus is capable to automatically identify fight scenes. Thereby helping in the
effective production of captivating movie highlights. We observe that the
proposed solution features 93.5% accuracy and is higher than 2D CNN with Hough
Forests which being 92% accurate and is significantly higher than 3D CNN which
features an accuracy of 65%.
