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Within both the natural world and constructed displays, our visual system transforms a raw image into objects and relations. Our lab explores this transformation: how we group objects together, how we know whether one object is larger, brighter or farther to the right than another, how many objects we can deal with at once, and how we track them over space & time.

Beyond their theoretical importance, these questions are vital to applications in education (e.g. graph understanding) and broader information visualization.

Projects

Selecting or tracking multiple objects at once may be limited only by ‘cortical’ spacing among the objects, setting a limit on individuation

The visual system can rapidly extract statistical information from scenes

Much of our newest work is on evaluating models of spatial relationship processing

 

Some types of similarity grouping, including common fate, may only happen for a single group at a time

We are exploring the potential role of the attentional ‘spotlight’ in influencing object structure

Our most recent work explores visual comparison in graphs and other visualizations

We are a member of NSF's Spatial Intelligence & Learning Center, dedicated to applying basic research to improving science education.

Lab news

Congrats to Lauren Kahn and Derek Tam for completing honors theses in the lab!

Franconeri receives NSF CAREER award grant, "Individuation in Visual Cognition".

Opportunities in the lab

A postdoctoral position is available in this laboratory.

We are always looking for enthusiastic undergraduates interested in learning about visual cognition research.