Fisheye Yolov4 Computer Vision Project
Updated 3 years ago
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Here are a few use cases for this project:
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Crowd Monitoring: The model could be used by security departments to monitor large crowds in public spaces, like parks, subway stations, and stadiums. With its ability to identify individual people even in crowded situations, it assists in analyzing crowd movement patterns or spotting suspicious activities.
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Social Distancing Compliance: Amid the COVID-19 pandemic, this model can be instrumental in enforcing social distancing norms. It can be used in malls, offices, schools, or restaurants to identify the concentration of people and ensure compliance with health protocols.
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Smart Home Security: The model can be implemented in home security systems to identify the presence of humans in certain areas of the house, alerting homeowners to possible intruders.
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Occupancy Control Systems: Establishments like libraries, gyms, or coworking spaces can use this model to monitor and regulate the number of users in a specific area at a given time, supporting occupancy management or limit enforcement.
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Public Space Design Research: By identifying the density and placement of people in places like parks or plazas, city planners and urban designers might use this model to obtain usage data, helping them design more user-friendly and efficient public spaces.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
fisheye-yolov4_dataset,
title = { Fisheye Yolov4 Dataset },
type = { Open Source Dataset },
author = { MoveCap },
howpublished = { \url{ https://universe.roboflow.com/movecap/fisheye-yolov4 } },
url = { https://universe.roboflow.com/movecap/fisheye-yolov4 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2021 },
month = { nov },
note = { visited on 2024-11-24 },
}