Object Recognition in Man, Monkey, and Machine

The contributors bring a wide range of methodologies to bear on the common problem of imagebased object recognition.These interconnected essays on threedimensional visual object recognition present cuttingedge research by some of the most creative neuroscientific, cognitive, and computational scientists in the field.Cassandra Moore and Patrick Cavanagh take a classic demonstration, the perception of twotone images, and turn it into a method for understanding the nature of object representations in terms of surfaces and the interaction between bottomup and topdown processes. Michael J. Tarr and Isabel Gauthier use computer graphics to study whether viewpointdependent recognition mechanisms can generalize between exemplars of perceptually defined classes. Melvyn A. Goodale and G. Keith Humphrey use innovative psychophysical techniques to investigate dissociable aspects of visual and spatial processing in braininjured subjects. D.I. Perrett, M.W. Oram, and E. Ashbridge combine neurophysiological singlecell data from monkeys with computational analyses for a new way of thinking about the mechanisms that mediate viewpointdependent object recognition and mental rotation. Shimon Ullman also addresses possible mechanisms to account for viewpointdependent behavior, but from the perspective of machine vision. Finally, Philippe G. Schyns synthesizes work from many areas, to provide a coherent account of how stimulus class and recognition task interact.The contributors bring a wide range of methodologies to bear on the common problem of imagebased object recognition.