Abstract

Address correspondence to T.P. The usual description of visual processing in cortex is an extension of the simple to complex hi-erarchy postulated by Hubel and Wiesel — a feedforward sequence of more and more complex and invariant features. The capability of this class of models to perform higher level visual processing such as viewpoint-invariant object recognition in cluttered scenes has been questioned in recent years by several researchers, who in turn proposed an alternative class of models based on the synchro-nization of large assemblies of cells, within and across cortical areas. The main implicit argument for this novel and controversial view was the assumption that hierarchical models cannot deal with the computational requirements of high level vision and suffer from the so-called “binding problem”. We review the present situation and discuss theoretical and experimental evidence showing that the perceived weaknesses of hierarchical models are not true. In particular, we show that recognition of multiple objects in cluttered scenes, arguably among the most difficult tasks in vision, can be done in a hierarchical feedforward model. 1

Citations