Orientation UV rPPG

A self-contained Python package containing the video processing module similar to that used in the paper Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation. For the full experimental code-base used to obtain the results in the paper please check out the experiments branch.

🔧 Installation

Prerequisites

• Python 3.10 or higher
• CUDA-compatible GPU (optional, but recommended for performance)

Install from GitHub

pip install git+https://github.com/csiro-internal/orientation-uv-rppg.git@package

💻 Quick Start

Basic Usage

The simplest way to use the package:

import torch
import orientation_uv_rppg as ouv

# Create video processor with custom parameters
processor = ouv.OrientationMaskedTextureSpaceVideoProcessor(
    min_detection_confidence=0.7,    # Higher confidence threshold
    min_tracking_confidence=0.8,     # More stable tracking
    device="cuda",                   # Use GPU acceleration
    output_size=128,                 # Higher resolution output
    degree_threshold=45.0            # Stricter orientation filtering
)

# Load your video frames
frames = torch.randn(200, 720, 1280, 3)  # HD video frames

# Process the video
result = processor(frames)
print(f"Input: {frames.shape}")
print(f"Output: {result.shape}")  # Should be [200, 128, 128, 3]

Please see the examples/ directory for usage examples and visualizations.

📜 Citation

If you find this useful please cite our work.

@inproceedings{cantrill2024orientationconditionedfacialtexturemapping,
      title={Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation}, 
      author={Sam Cantrill and David Ahmedt-Aristizabal and Lars Petersson and Hanna Suominen and Mohammad Ali Armin},
      booktitle={Proceedings of the IEEE/CVF Computer Vision and Pattern Recognition Workshops}
      year={2024},
      url={https://openaccess.thecvf.com/content/CVPR2024W/CVPM/papers/Cantrill_Orientation-conditioned_Facial_Texture_Mapping_for_Video-based_Facial_Remote_Photoplethysmography_Estimation_CVPRW_2024_paper.pdf}, 
}