Michelin GT Computer Vision Project
Updated a year ago
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Here are a few use cases for this project:
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Sponsorship Detection: The Michelin GT model could be used to identify logos during racing events, whether they're video game streams or real-world broadcasts. The system could be used by brand sponsors like Michelin, Goodyear, or Dunlop to monitor their logo exposure, to estimate the value of these branding opportunities.
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eSports Analytics: The model could be employed in analyzing in-game advertising effectiveness within eSports or online gaming streams. Game developers or publishers can use this information to understand how often and for how long sponsored logos appear on their users' screens.
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Branding Compliance: Within advertising or promotional materials, it's essential to ensure appropriate usage of a brand's logo. The application of the Michelin GT model could help companies automatically verify if their logos' representation follows their corporate identity guidelines, especially in large scale events like car races or video games.
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Aiding Augmented Reality (AR) Experiences: The model can be used to trigger AR experiences once a specific logo like 'Michelin bibendum' or 'Pneu Goodyear' is detected. For example, pointing at a Michelin logo with a mobile device may provide additional info about the brand, the product, or nearby shops.
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Automated Cataloguing of Media Assets: Businesses working with large volumes of images or video content could use the Michelin GT model to tag and categorize their media files more accurately, resulting in a more efficient content retrieval process.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
michelin-gt_dataset,
title = { Michelin GT Dataset },
type = { Open Source Dataset },
author = { tmfErwan },
howpublished = { \url{ https://universe.roboflow.com/tmferwan/michelin-gt } },
url = { https://universe.roboflow.com/tmferwan/michelin-gt },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-11-08 },
}