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Human 3D Pose Estimation and Visualization

This project implements a pose tracking system using MediaPipe for real-time pose estimation. The system supports both webcam and RealSense cameras, allowing for both 2D and 3D visualization of tracked landmarks.

Overview

The pose_estimation.py script serves as the main entry point for the application, initializing the camera, processing video frames, and visualizing pose landmarks. The pose_visualiser.py script provides a 3D visualization environment for the detected pose points and camera orientation.

Features

  • Real-time pose tracking using MediaPipe
  • Support for webcam and RealSense cameras
  • 2D and 3D visualization of pose landmarks
  • Depth awareness when using depth-capable cameras
  • Interactive visualization with mouse controls

Installation

To run this project, ensure you have the following dependencies installed (requirements.txt). In some versions there is a backend conflict between Pyqt5 and opencv, therefore i have mentioned specific versions for the same.

Usage

To start the pose tracking application, run the following command in your terminal: python pose_estimation.py --cam-type <realsense|webcam> --depth --model <lite|full|heavy> --width <width> --height <height>

Arguments

  • --cam-type: Specify the type of camera to use (default is realsense).
  • --depth: Enable depth processing (only applicable for depth cameras).
  • --model: Choose the model type for pose estimation (default is lite).
  • --width: Set the width of the video frame (default is 640).
  • --height: Set the height of the video frame (default is 480).

Example

python pose_estimation.py --cam-type webcam --model lite --width 640 --height 480

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

  • This project uses MediaPipe for pose estimation.
  • 3D visualization is powered by Vispy.