Human_Pose_Detection Computer Vision Project
Updated 2 years ago
Metrics
Here are a few use cases for this project:
-
Fitness and Physical Therapy: The Human_Pose_Detection model can be used to track and analyze body postures during various exercises and physical therapy sessions, allowing trainers and therapists to monitor progress, provide feedback, and ensure that proper techniques are being utilized to prevent injuries.
-
Smart Home Automation: Integrating the model into smart home systems can improve user experience by adapting the environment according to the detected poses, such as adjusting lighting based on whether a person is sitting, standing or sleeping, or automating appliances based on detected activities like moving or eating.
-
Security and Surveillance: The model can be used to monitor public spaces or private properties for unusual activities or trespassers by analyzing human poses and detecting any suspicious behavior, such as prolonged sleeping in public areas or people running in restricted zones.
-
Elderly and Disabled Care: Utilizing the Human_Pose_Detection model within care facilities or home monitoring systems can assist caregivers in tracking the activities and movements of elderly or disabled individuals, enabling early detection of falls, unusual sleeping patterns or potential health issues.
-
Workplace Ergonomics: By analyzing employee postures in office or industrial settings, the model can help identify potential ergonomic issues or assess the effectiveness of current workplace layouts, enabling companies to improve safety, comfort and productivity for their employees.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
human_pose_detection_dataset,
title = { Human_Pose_Detection Dataset },
type = { Open Source Dataset },
author = { Emam Hossain },
howpublished = { \url{ https://universe.roboflow.com/emam-hossain-0ooei/human_pose_detection } },
url = { https://universe.roboflow.com/emam-hossain-0ooei/human_pose_detection },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { mar },
note = { visited on 2024-11-21 },
}