COMPSCI 180 Final Project 2: Eulerian Video Magnification

Aishik Bhattacharyya & Kaitlyn Chen

Introduction:

This project aims to amplify temporal color variations in videos to emphasize aspects of the video. For instance we can amplify blood flow and low-amplitude motion. To amplify these parts, which are not easy to see with just the human eye, we examine changes at particular temporal frequencies. These frequencies correspond to a certain beats per minute. This project follows the paper “Eulerian Video Magnification for Revealing Subtle Changes in the World”.

Laplacian pyramid:

We first need to compute a laplacian pyramid for every frame in the input video. We can build a laplacian pyramid, following that of previous projects. First calculating the gaussian pyramid, downsampling each level, then upsample and subtract consecutive gaussian levels to create the laplacian pyramid. This highlights the regions of rapid intensity change. We can also reconstruct the image from the laplacian pyramid by simply upsampling and adding levels of the pyramid.

Temporal Filtering:

We need to then create the temporal filter. On every level of the laplacian stack, we convert to the frequency domain using FFT, apply a bandpass filter to its frequencies, convert it back to the time domain, amplify it and add it back to the original value (Pixel change magnification).

Image reconstruction:

Finally, we reconstruct the image by looping over every frame, pulling its respective values from the laplacian stack and summing up its upsampled results. We use cv2 to read and write our videos.

Results of amplifying temporal color variations in provided face and baby videos (using parameters: depth=4, f_min=0.83, f_max=1, fps=30, alpha=10) :

Amplifying variations in our own video of a wrist vein (using the same parameters as above):

We can some difficulty testing the code since our outputted video came at the very end, so we had to utilize many print statements to ensure the colorations of our final video were accurate.