Current research: vision

I study aspects of visual learning and generalization involving complex structured objects. My work focuses on visual categories exhibiting high degrees of internal variation within abstract structural constraints. Unlike other well-studied object types (e.g. faces), complex structured objects (e.g. houses) are not well-captured by template-based recognition models, which assume a rigid set of elementary subparts. We use Bayesian inference on grammar-based representations to explain the rapid and subconscious knowledge acquisition concerning these objects in the visual domain.
Coming soon
“A Grammar-Based Approach to Visual Category Learning,”
Proceedings of CogSci 2008
July 23-26, 2008
Washington, DC