Armed with knowledge about how humans perceive visualizations, we are building computational tools to reason about posters, graphs, and visualizations, with applications to design, advertising, and user interfaces.

We are using state-of-the-art deep learning approaches to automatically detect and parse text inside posters, to look around an image to automatically detect representative visual pictographs or icons, and to make predictions about the topics or concepts being communicated. We can make predictions about where people look on posters and graphs, and use this information to automatically generate text and visual summaries and thumbnails. Our approaches can be made to work in real-time within interactive design applications.