A Three-Feature Model to Predict Colour Change Blindness

TL;DR

This paper presents a simple, automated three-feature linear regression model that predicts colour change blindness in images, correlating well with actual detection times and classifying stimulus difficulty.

Contribution

It introduces a novel, minimalistic model using only three features to predict colour change blindness and classify stimulus difficulty.

Findings

Model correlates significantly with measured detection times

Effective in classifying stimuli by difficulty

Uses only two low-level features and observer experience

Abstract

Change blindness is a striking shortcoming of our visual system which is exploited in the popular "Spot the difference" game. It makes us unable to notice large visual changes happening right before our eyes and illustrates the fact that we see much less than we think we do. We introduce a fully automated model to predict colour change blindness in cartoon images based on two low-level image features and observer experience. Using linear regression with only three parameters, the predictions of the proposed model correlate significantly with measured detection times. We also demonstrate the efficacy of the model to classify stimuli in terms of difficulty.