Video Data Collection and Curation for Two-wheeler Vehicles Computer Vision Project
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Here are a few use cases for this project:
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Autonomous Vehicles Navigation: This model could be vital in recognizing obstacles for self-driving two-wheeler vehicles. These vehicles could use the model to identify potential road hazards and navigate around them safely.
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Road Maintenance and Safety: Local municipalities or city planning teams could use this model to proactively identify and repair road damage like potholes, subsidence, or loose surfaces, thus improving road safety.
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Augmented Reality Touring: This model can be used in AR-based touring applications to provide cyclists or motorbike riders with real-time updates about upcoming obstacles or potential hazards on their route.
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Game Development: Developers of driving or biking simulation games can use this model to make their virtual environments more realistic by including a diverse array of street obstacles that players must avoid.
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Insurance claim processing: Insurance companies could utilize this system to assess the validity of claims related to two-wheeler accidents. The system could analyze video data to determine if reported obstacles were indeed present and had contributed to the accident.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
video-data-collection-and-curation-for-two-wheeler-vehicles_dataset,
title = { Video Data Collection and Curation for Two-wheeler Vehicles Dataset },
type = { Open Source Dataset },
author = { University of Canberra ITS project },
howpublished = { \url{ https://universe.roboflow.com/university-of-canberra-its-project/video-data-collection-and-curation-for-two-wheeler-vehicles } },
url = { https://universe.roboflow.com/university-of-canberra-its-project/video-data-collection-and-curation-for-two-wheeler-vehicles },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { apr },
note = { visited on 2024-11-21 },
}