Anna Chinni¹, Y. Ivette Colón¹, Kushin Mukherjee¹, Michael Gleicher¹, Karen B. Schloss¹; ¹University of Wisconsin - Madison

Texture is useful for representing categorical data in information visualizations, especially when color display capabilities are limited (He et al., 2024). Prior work on texture for visualization mostly focused on which dimensions of texture could represent data effectively, with little focus on texture semantics—the meaning people ascribe to textures. To study texture semantics (cf. color semantics; Schloss (2024), we need a library of visual textures that are relatively uniform, are perceptually discriminable, and span dimensions of texture perception. To develop such a library, we began with the Normalized Brodatz Texture (NBT) database, a standard set of texture images that have been normalized for lightness (Abdelmounaime & Dong-Chen, 2013). We aimed to subset the 112 textures to select textures that were (1) uniform over the image (important for future use in data visualizations) and (2) perceptually dissimilar. Toward these goals, we first asked participants to rate the uniformity of each texture, and we excluded textures that were, on average, below the neutral point of the rating scale. To assess the similarity of the remaining 62 textures, we asked a second group of participants to make triplet similarity judgements. Using data from over 11,000 trials across 59 participants, we estimated a 3-dimensional embedding of the textures that best explained human judgements (Sievert et al., 2023). Although similar embeddings exist for a subset of the original non-normalized Brodatz textures (Ravishankar Rao & Lohse, 1996), we reasoned that the dimensions could be different for the normalized images. The 3-dimensions of our embedding were: fine/course, hard/soft, and random/non-random (named using data from different participants). Finally, we used k-means clustering on this embedding to identify highly similar textures and selected the most uniform texture within each cluster. This approach yielded a final set of 53 textures, which we call the NBT-53 texture library.

Acknowledgements: NSF award BCS-2419493 to K.B.S.