The images for this video were prepared and transformed by Michael Notter.
In a first step, Michael used the machine learning library dlib and some custom Python code to detected in each of Noah’s photos 5 face landmarks (i.e. both eyes, the nose and the two corners of the mouth). These landmarks were then used to align the faces in all photos, so that the eyes and corner of the mouth were horizontally oriented and always an equal distance apart. After that, some small image intensity correction were applied to make very dark images a bit brighter and very bright ones a bit darker. This was followed by an upscaling of all images (where needed) to a 4K resolution.
In a second step, once the faces were upscaled and aligned, Michael looped through all of the images and averaged them with a sliding window approach: Each frame in the video shows the average face of the last 60 faces. Or in other words, each frame shows the ‘average Noah’ over the last 2 months. With a video frame rate at 60Hz, this means Noah ages in this video 2 month every second, or 10 years every minute.