basketball_child Computer Vision Project
Updated a year ago
Here are a few use cases for this project:
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Sports Training: The "basketball_child" model can be used to track and analyze the movements, shots, and gaming strategies of young basketball players, offering valuable insights to coaches and trainers to improve training programs based on individual performance.
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Player Detection: For security or performance monitoring, this model can help detect particular players in a crowded playground by tracking the ball, rim and the player involved.
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Augmented Reality Games: It can be incorporated in creating AR-based basketball games for children, providing a more interactive and immersive gaming experience by identifying the virtual ball and rim movements.
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Video Analysis: It can be utilized to analyze and index basketball match videos, which could be valuable for scouting or performance review. It could evaluate takes and misses contributing to statistics generation in real-time.
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Automated Video Production: In live broadcasts or recorded content of basketball matches, the model can be used for automatic camera control, following the ball, the rim and players across the court to ensure high-quality coverage.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
basketball_child_dataset,
title = { basketball_child Dataset },
type = { Open Source Dataset },
author = { AI },
howpublished = { \url{ https://universe.roboflow.com/ai-79z1a/basketball_child } },
url = { https://universe.roboflow.com/ai-79z1a/basketball_child },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { sep },
note = { visited on 2024-11-21 },
}