Real-Time Pose Estimation for Augmented Reality Gaming

Description

This project leverages Computer Vision and Deep Learning to perform real-time pose estimation for augmented reality (AR) gaming. By tracking and analyzing human body movements, the system can enhance gaming experiences by enabling precise interactions with virtual environments.

Features:

• Detects and tracks key human body points (e.g., joints).
• Real-time processing for seamless integration into AR applications.
• High accuracy and efficiency using state-of-the-art models like OpenPose or Mediapipe.
• Customizable for gaming environments and fitness applications.

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Tags

#PoseEstimation #ComputerVision #AugmentedReality #DeepLearning #Gaming 
#RealTimeProcessing #AI #HumanPoseDetection #OpenPose #Mediapipe

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Documentation

1. Prerequisites

Install necessary libraries:

pip install opencv-python mediapipe numpy matplotlib

2. Running the Project

1. Clone the repository:

   git clone https://github.com/bashitalishaikh/pose-estimation-ar-gaming.git

2. Navigate to the project folder:

   cd pose-estimation-ar-gaming

3. Run the main script:

   python pose_estimation.py

3. Key Components

• Pose Detection Module: Detects key points on the human body in real time.
• AR Integration Module: Maps body movements to AR game controls.
• Visualization: Displays pose estimation overlays on video input.

4. Models Used

• Mediapipe Pose: Lightweight and fast for real-time applications.
• OpenPose: High accuracy for detecting multiple poses.

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Future Aspects

1. Enhanced Interactivity:

   • Introduce gesture-based controls for AR games.
   • Integrate voice commands for an immersive experience.

2. Scalability:

   • Adapt for multiplayer environments.
   • Extend for motion capture in fitness and healthcare.

3. Optimized Performance:

   • Utilize GPU acceleration for faster processing.
   • Develop mobile-friendly versions for AR gaming on smartphones.

4. Application Domains:

   • Fitness tracking and personalized workout recommendations.
   • Virtual reality (VR) integration for immersive experiences.

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Contribution

Feel free to open an issue or submit a pull request. Contributions are welcome!

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Contact

Maintainer: [Your Name]

• LinkedIn
• Email
• Repository: GitHub Link

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📊 RESULTS

🔗 References

• YOLOv7 Repo: https://github.com/WongKinYiu/yolov7
• Ultralytics: https://github.com/ultralytics/yolov5

📖 Articles

• YOLOv7 Training Guide
• Computer Vision Roadmap