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Bibliographic Details
Main Author: Mathur, Aryan
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.05152
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author Mathur, Aryan
author_facet Mathur, Aryan
contents 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%.
format Preprint
id arxiv_https___arxiv_org_abs_2406_05152
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Fight Scene Detection for Movie Highlight Generation System
Mathur, Aryan
Computer Vision and Pattern Recognition
Machine Learning
Image and Video Processing
Signal Processing
F.2.2, I.2.7
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%.
title Fight Scene Detection for Movie Highlight Generation System
topic Computer Vision and Pattern Recognition
Machine Learning
Image and Video Processing
Signal Processing
F.2.2, I.2.7
url https://arxiv.org/abs/2406.05152