Attached is an algorithm that can quickly take a dataset of videos, and generate a new sequence of frames from those videos that looks very realistic. In short, given a dataset of videos, this algorithm can generate a new video, with frames taken from each of the original videos, and reassemble them in a manner that looks very realistic. I’m still tweaking this, but it works, and the results are quite cool.

The concept is more general, and I plan on using it to produce novel images given datasets of images, in particular, datasets of paintings. This approach appears to be a very fast substitute for the types of composite images that are generated by neural networks. On the dataset below, this algorithm runs in about 2 seconds.

The image files for the video I used can be found on dropbox.

The actual command line script is below:

Imitate_Data_NN

Regrettably, I’m having some issues with my researchgate page, and it looks like all attachments have simply disappeared. A decent amount of my code is still available on this blog, but if you need a particular script, feel free to send me a message.