EvoColour is an exciting new citizen-science project that explores human perception of colour and beauty. It takes the form of a web based experiment that everyone (including you!) can participate in, through your web browser. By aggregating the opinions of many different people over the web, EvoColour elicits the ‘wisdom of the crowds’ to find colour combinations and patterns that are generally accepted as being pleasing (as well as finding those that are not pleasing).

Why not have a go? Visit the project website!

How does it work?

When visitors come to the do the study, they are presented with a series of pairs of images. Each image consists of concentric circles of (up to 3) colours in varying proportions and patterns. For example:

EvoColour screenshot

Users simply click on the image they prefer, or indicate that they have ‘no preference’. They are then presented with another pair of images. This is done over and over as many times as they like.

In taking part in this study, the visitors are driving what’s called a genetic algorithm, which mimics how evolution and natural selection operate in nature. The more popular images, then ones that have been selected most often by most users, are deemed to be the ‘fittest’ images, and they then are selected for survival. Meanwhile the unpopular images, images that have not been preferred by the users, die off. The surviving images then breed and pass on their characteristics to their children, which form the next generation of the population. In this way, populations of images evolve to have characteristics that the crowds deemed to be more pleasing.

By analysing the evolving populations of images, we can answer a number of questions; are there certain colour combinations and patterns that are significantly accepted as more pleasing? If so what are the attributes of these popular colour palettes?

For more info (and to give it a try!), please visit the EvoColour website!

This is the most popular image on EvoColour right now!

I’m a musician, researcher, sound designer, composer and software engineer. My research explores frameworks for parameter discovery in generative design, with an emphasis on crowdsourcing and the modeling of aesthetic preferences.

Current research topic: Parameter Search for Aesthetic Design and Composition

Strategies for parameter discovery in aesthetic tasks, with emphasis on crowdsourcing.