Summary of Fight Scene Detection For Movie Highlight Generation System, by Aryan Mathur
Fight Scene Detection for Movie Highlight Generation System
by Aryan Mathur
First submitted to arxiv on: 4 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG); Image and Video Processing (eess.IV); Signal Processing (eess.SP)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research project proposes a novel Fight Scene Detection (FSD) model using Bidirectional Long Short-Term Memory (BiLSTM) networks, which can be applied to Movie Highlight Generation Systems (MHGS) based on deep learning and Neural Networks. The FSD system leverages temporal characteristics of movie scenes to automatically identify fight scenes, facilitating the production of captivating movie highlights. The proposed solution achieves 93.5% accuracy, outperforming 2D CNN with Hough Forests (92%) and 3D CNN (65%). |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers created a new way to find fight scenes in movies using special kinds of artificial intelligence called BiLSTMs. This helps make highlight reels for movies that are exciting and interesting. Instead of having people manually search through the movie, this system can do it automatically. The results show that this method is very accurate, working better than other approaches. |
Keywords
» Artificial intelligence » Cnn » Deep learning
