We’re returning for our third biennial installment of visXvision at IEEE VIS.
Our workshop will cover the latest at the intersection of vision science and visualization research, providing the opportunity for researchers in both communities to update their understanding of this cross-disciplinary research and discover avenues for new collaborations.
Stay tuned to our page on VIS 2023 for more details!
Sponsored by: Adobe Inc., CU Boulder VisuaLab, Northwestern U Visual Thinking Lab
Following the last three years of fun interdisciplinary events at both VIS and VSS, we are holding the first official event for vision scientist and visualization researcher collaboration, interaction, and peer reviewed research-sharing at VIS. The specific goal of this workshop is to provide a forum where vision science and visualization researchers can share cutting-edge research at this interdisciplinary intersection, in preparation for publishing and presenting it at both IEEE VIS, as well as in the upcoming Journal of Vision Special Issue.
Short Papers:
Note: paper drafts can be downloaded via IEEE Xplore and here with the workshop password.
Invited Speaker Abstracts and Slides:
Visual search– Jeremy Wolfe
If you want people to find “it”, what should “it” look like?
Decades of research on visual search have given us quite a good understanding of how people look for targets in scenes containing distracting items. Knowing how people search is not the same as knowing how to design searchable visual stimuli, especially if we want users to be able to search those stimuli for a variety of different targets. Still, the topics of search and searchability must be related so we will explore what the rules governing the deployment of visual attention might suggest to the creators of new visualizations.
Working memory– Timothy Brady
When processing complex visual displays, people often need to hold information actively in mind to facilitate comparison or integration. Decades of research have shown that our ability to hold information actively in mind is incredibly limited (e.g., we can miss large changes to scenes if we happen to not be holding in mind the right information), and simple rules like people can remember 3-4 things are popular ways to conceive of these limits. In this talk, I discuss what aspects of visual information people can easily hold in mind; what things are extremely difficult to hold in mind; and how these limits relate to visualization design.
Visual magnitudes– Darko Odic
How perception perceives number, time, and space.
The perception of visual magnitudes – length, area, time, number, etc. – has been one of the foundational questions since the dawn of empirical psychology, stretching back from Weber and Helmholtz to today. In this talk, I will share a number of insights, new and old, about how we perceive number, time, and space representations throughout our entire lifespan, focusing especially on issues that might be relevant for data visualization. I will first discuss findings about how our perceptual system deals with competing magnitude dimensions: situations in which, e.g., both number and length are competing for attention. Next, I will share several findings demonstrating that surface area perception is susceptible to various surprising inconsistencies and illusions, whereby we perceive collections of objects to be cumulatively smaller than they really are. Finally, I will share findings on how perceptual magnitude representations allow us to easily find the maximal and minimal element in a set.
Thanks to everyone who attended this event!
“Discover Pasteur’s Quadrant: Four research communities that will inspire your work”. (FYI- we’re expecting video + slides to be posted on the OPAM website sometime soon- for now, find a link to the program here).
Tamara Munzner‘s panel talk, “Data Visualization as a Driver for Visual Cognition Research“, was declared (by the OPAM keynoter Jeremy Wolfe) to open millennia-worth of dissertation material for visioneers. Find her slides here!
Presenters shared lightning talks about their latest work at the intersection of vision science and visualization!
Abstract archives and presentation slides can be found here:
| Presenter Name | Topic |
|---|---|
| Fumeng Yang | Correlation Judgment |
| David Burlinson | Open vs Closed Shapes |
| Maureen Stone | Color Design for Tableau 10 |
| Steve Haroz | From Spatial Frequencies to ISOTYPE |
| Alex Kale | Uncertainty in Visualizations |
| Nam Wook Kim | BubbleView |
| Zoya Bylinskii | Predicting Attention for Design Feedback |
| Christie Nothelfer | How Do We Read Line Charts? |
| Madison Elliott | Task Demands Affect Feature Selection |
Read our full panel submission with abstracts here!
Panelist Bios and Talk Slides:
Peripheral Vision and Usability
Ruth Rosenholtz is a Principal Research Scientist in MIT’s Department of Brain and Cognitive Sciences, and a member of CSAIL. She has a B.S. in Engineering from Swarthmore College, and an M.S. and Ph.D. in EECS from UC Berkeley. Her lab studies human vision, including visual search, perceptual organization, visual clutter, and peripheral vision. Her work focuses on developing predictive computational models of visual processing, and applying such models to design of user interfaces and information visualizations. She joined MIT in 2003 after 7 years at the Palo Alto Research Center (formerly Xerox PARC).
Visualization and Vision Science.
Ronald Rensink is an Associate Professor in the departments of Computer Science and Psychology at the University of British Columbia (UBC). His research interests include visual perception (especially visual attention), information visualization and visual analytics. He obtained a PhD in Computer Science from UBC in 1992, followed by a postdoc in Psychology at Harvard University, and then several years as a scientist at Cambridge Basic Research, an MIT-Nissan lab in Cambridge MA. He is currently part of the UBC Cognitive Systems Program, an interdisciplinary program combining Computer Science, Linguistics, Philosophy, and Psychology.
Steven Franconeri is Professor of Psychology at Northwestern University, and Director of the Northwestern Cognitive Science Program. His lab studies visual thinking, graph comprehension, and data visualization. He completed his Ph.D. in Experimental Psychology at Harvard University with a National Defense Science and Engineering Fellowship, followed by a Killam Postdoctoral Fellowship at UBC. He has received the Psychonomics Early Career Award and an NSF CAREER award, and his work is funded by the NSF, NIH, and the Department of Education.
A Color Inference Approach to Interpreting Colors in Information Visualization.
Karen Schloss is an Assistant Professor at the University of Wisconsin – Madison in the Department of Psychology and Wisconsin Institute for Discovery. Her Visual Perception and Cognition Lab studies color cognition, information visualization, perceptual organization, and navigation in virtual environments. She received her BA from Barnard College, Columbia University in 2005, with a major in Psychology and a minor in Architecture. She completed her Ph.D. in Psychology at the University of California, Berkeley in 2011 and continued on as a Postdoctoral Scholar from 2011-2013. She spent three years as an Assistant Professor of Research in the Department of Cognitive, Linguistic, and Psychological Sciences at Brown University before joining the faculty at UW – Madison in 2016.
InfoVis x Vision science 