When I launched this site over two years ago, one of my first decisions was to pick a color scheme – it didn’t take long. Anyone who watches enough film becomes quickly used to Hollywood’s taste for oranges and blues, and it’s no question that these represent the default palette of the industry; so I made those the default of BoxOfficeQuant as well. But just how prevalent are the oranges and blues?

Some people have commented and researched how often those colors appear in movies and movie posters, and so I wanted to take it to the next step and look at the colors used in film trailers. Although I’d like to eventually apply this to films themselves, I used trailers because 1) They’re our first window into what a movie will look like, and 2) they’re easy to get (legally). So I’ve downloaded all the trailers available on the-numbers.com, 312 in total – not a complete set, but the selection looks random enough – and I’ve sampled across all the frames of these trailers to extract their Hue, Saturation, and Value. If you’re new to those terms, the chart below should make it clear enough: Hue is the color, Value is the distance from black, (and saturation, not shown, is the color intensity).

After sampling, I created the chart below to represent the distribution of those colors, so we could truly see how often they appear. I’ve weighted each pixel by the length of the trailer (so longer trailers aren’t overrepresented), and by the value and saturation (because even if the Hue is red, if the value is so low that it’s nearly black, then we don’t perceive much red being there), and so each bar below represents the prevalence of that bar’s color.

This chart makes it visually clear that the oranges and blues truly dominate movie trailers, and which shades exactly are represented. It’s also worth noting that of this graphic is just a histogram, which is a common chart in statistics to measure probabilities, but usually has more function than form. Below, I wanted to dive a little deeper into individual film trailers, displaying their average Hues and Values, their individual spectra, and the distributions of reds, greens, and blues. Scroll over each dot for the film title, and click for more information.

Finally, I wanted to note that this post began as a project for a class in Machine Learning along with my very talented classmate, Qinghui Ji. For the project, we sampled data from trailers to see if movie genre is predictable from colors, subtitles, and face recognition. And our results can be found here, for anyone curious about a more intensive look at the information contained in trailers.

Notes:

All trailers are from the-numbers.com, the Python OpenCV package was used to decode the videos, and the charts were made with ggplot2 and Protovis.