In this talk, I will describe a computational framework for the study of visual perception. I will present computational as well as experimental evidence suggesting that bottom-up and top-down processes make a distinct and essential contribution to the recognition of complex visual scenes. A feedforward hierarchical architecture may provide a satisfactory account of “immediate recognition” corresponding to the first few hundred milliseconds of visual processing. However, such an architecture may be limited in recognizing complex visual scenes. I will show how attentional mechanisms and cortical feedback may help improve object recognition performance in complex cluttered scenes.

Host: Luis Bettencourt, T-5