Projects

The main projects in our lab aim to understand the associations people have between perceptual features and concepts and how they use those associations to make judgments about the world.

Associations between visual features and concepts are at the core of visual reasoning. Evidence suggests that color-concept associations are the basis on which people (1) evaluate preferences for colors and (2) interpret meanings of colors in information visualizations. The link between color-concept associations and these seemingly different types of judgements can be understood within the Color Inference Framework (Schloss, 2018; 2024). The framework posits that people continually form and update their associations between colors and concepts through color-related experiences in the world. These associations can be represented in a network that stores associations between all possible colors and concepts. Different kinds of inference operations are computed on the color-concept association network to produce different kinds of judgments: pooling produces preferences for colors and assigning determines interpretations of the meanings of colors in visual encoding systems.

Our research on color-concept associations has key objectives. First, we aim to understand how people form color-concept associations through their experiences in the world. Second, we aim to develop efficient ways of quantifying color-concept associations by leveraging image databases and computational modeling. With good estimates of color-concept associations, we will be able to produce more comprehensive predictions about how these associations contribute to visual reasoning.