Horse Racing level 2 Computer Vision Project
Updated 3 years ago
Here are a few use cases for this project:
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Sports Analytics: The "Horse Racing Level 2" model can be utilized for breaking down video or images from horse races, identifying key features such as the horse's body, number labels, or helmets. This could assist in providing real-time race statistics, horse performance analysis, and tracking the jockey's control by scrutinizing his movement and head orientation.
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Betting Applications: Computer vision model could be utilized in the creation of platforms for horse racing betting. It can collect data about the horses and their jockeys during the races, enabling users to make informed bets based on a horse's performance or a jockey's strategy visualized by the model.
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Training Enhancement: Trainers could use this model to monitor and analyze a jockey's form and the horse's performance during training sessions. This could provide crucial insights for improving techniques, strategy and overall performance.
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Media Coverage: Media outlets could use this model to enhance the viewer's experience by offering deeper insights into the race such as visualizing the number labels, horse details or helmet analysis for audience's better understanding of the race.
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Event Security: At horse racing events, security officials can use this model to identify specific jockeys or horses based on their helmets and label numbers, respectively. This could assist them in monitoring activities in crowded situations or controlling access to certain areas.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
horse-racing-level-2_dataset,
title = { Horse Racing level 2 Dataset },
type = { Open Source Dataset },
author = { new-workspace-vyhrr },
howpublished = { \url{ https://universe.roboflow.com/new-workspace-vyhrr/horse-racing-level-2 } },
url = { https://universe.roboflow.com/new-workspace-vyhrr/horse-racing-level-2 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { jan },
note = { visited on 2025-02-03 },
}