mapping_football_five Computer Vision Project
Updated a year ago
Metrics
Here are a few use cases for this project:
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Sports Analytics: This model could be used to track the performance and movement patterns of individual players, goalkeepers, and the ball during a live game or post-match analysis. Useful metrics could include ball possession time, player positions, strategies etc.
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Interactive Sports Games Creation: The model could provide critical inputs for developing realistic sports video games or AR/VR experiences by taking real-world player data and integrating it into the gaming environment.
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Training and Coaching: Coaches could utilize this model to analyze team strategies and training sessions, tracking players' movements and their interaction with the ball. Visualization of these dynamics could inform and improve training techniques and game plans.
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Sports Governance: The model could contribute in real-time decision making, foul detection and rule violation identification in football games, aiding referees and sports governing bodies.
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Media and Spectator Experience: Media companies could leverage this model to enhance the viewing experiences of spectators, by providing real-time, detailed analysis of the game progression including player movements and ball handling.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
mapping_football_five_dataset,
title = { mapping_football_five Dataset },
type = { Open Source Dataset },
author = { Centrale Lyon },
howpublished = { \url{ https://universe.roboflow.com/centrale-lyon-dpp7c/mapping_football_five } },
url = { https://universe.roboflow.com/centrale-lyon-dpp7c/mapping_football_five },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2024-11-13 },
}