Our paper “Context matters: A theory of semantic discriminability for perceptual encoding systems” received Honorable Mention for best paper at IEEE VIS 20211!
This paper presents semantic discriminability theory, a new theory on constraints for generating semantically discriminable perceptual features for encoding systems that map perceptual features to concepts. We provided evidence supporting two hypotheses that arise from the theory. First, the capacity to create semantically discriminable color palettes for a set of concepts depends on the difference in color-concept association distributions between those concepts, independent of properties of the concepts alone. Second, people can accurately interpret mappings between colors and concepts for concepts previously considered “non-colorable,” to the extent that the colors are semantically discriminable. Although we focused on color in this study, the theory has potential to extend to other types of visual features (e.g., shape, orientation, visual texture) and features in other perceptual modalities (e.g., sound, odor, touch).
Reference: Mukherjee, K., Yin, B., Sherman, B. E., Lessard, L. & Schloss, K. B. Context matters: A theory of semantic discriminability for perceptual encoding systems. IEEE Transactions on Visualization and Computer Graphics. PDF
Our new article on how people interpret messages in color-coding systems was published in Cognitive Research: Principles and Implications (CRPI).
Our new article on using color space metrics to describe and predict patterns of color preference is now published online in Vision Research. 
Our new article presenting a unified framework for understanding temporal and individual differences in color preferences is now published online in Vision Research. 
Our new article reporting on how color preferences change with the seasons was just published in Cognitive Science’s Early View online.