Computer Vision Project 2020

Welcome to the repository of our Computer Vision project !

The project was initiated as an academic project at CentraleSupélec during the Computer Vision course.

The goal of the project is to use Computer Vision methods to detect the heartbeat of someone using a video of their face. The heartbeat is detected simply by using the color variation of the face, which becomes redder once per heartbeat.

The video is processed in 3 steps : spatial processing, temporal processing (using a bandpass filter) and the final merge operation. More details about this in our report !

After the video is processed, you obtain the value of the bpm and a video where the color variation of the face (variation of red intensity) are exagerated, to make the heartbeat visible.

This project is mainly based on a thesis about Video Magnification from the MIT : http://people.csail.mit.edu/mrub/vidmag/.

Run the project

Prerequisites

Before being able to run this project, you need to fulfill the following requirements:

• Python 3.8

The following Python module are required :

• NumPy and SciPy
• OpenCV

Detect a hearbeat - oh god it's alive !

The project does not have any CLI or GUI.

To use it simply edit the parameters in the main.py file :

• source_path is the path of the source video file in which you want to highligh the heartbeat of someone
• out_path is the path of the output video
• downsample_level is the number of time you will perform the blur and downsampling operations for the spatial processing
• lowcut, highcut, fs and order are for the bandpass filter
• alpha, chrome_attenuation and distance_threshold are for the merge operation at the end

You should probably just change the source_path and the out_path, but maybe changing the other parameters will help you get a better result for your specific case.

And then run the main.py using :

python main.py

For better result, you should use a video which shows only the face of one people, standing as still as possible.

Built With

The whole project is written in Python 3.

Contributing

This project does not accept public contributions.

Authors

• Hackatosh
• damianib
• Zizol

License

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

Acknowledgments

• Thanks to CentraleSupélec.
• Thanks to the people at the MIT who made the thesis and the original implementation in C.