Inspired by Nordlicht I made a small program that finds the most dominant colors in movies. Using k-means clustering, it builds a color palette with 32 colors and calculates the number of pixels with smallest distance to the cluster centers.
As it would be far too computationally expensive if clustering worked on the complete set of full-sized images of a movie, I only extracted one frame per second and scaled it down to 16×16 pixels. Moreover, I cropped black borders from each frame, and removed all logos at the beginning as well as the credits at the end. This avoids having meaningless black pixels in the clustering process.
Some results are shown in the following images. The pie charts show the colors and their frequency of occurence. The bar below shows just the colors.
Big Buck Bunny
District 9
The Lord of the Rings: The Fellowship of the Ring
Mad Max: Fury Road
Shrek
Star Wars: Episode I – The Phantom Menace
Star Wars: Episode IV: A New Hope
The Dark Knight
The Social Network
The code is on GitHub. The D3-based generator for the pie charts can also be found on JSBin.
Tags: clustering, colors, k-means, movies
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