The big problem for visual systems is to signal the properties of relevant objects in the field of view, and to “ignore” the variable nature of the light falling on the objects. There is evidence for the optimisation of colour vision for achieving these kinds of aims, for specified important tasks, such as foraging for food. However, it is an open (and interesting) question whether, and when, aspects of illumination such as shadows are ignored in human vision. I will describe a series of experiments and computational studies which address this issue, and conclude that the issue is much more rich than was previously assumed.

Tom Troscianko originally studied Physics, and became a research scientist at Kodak Ltd, studying colour vision and photography. He did a PhD in the Department of Optometry and Visual Science at The City University, London after which (in 1978) he came to Bristol University to work with Richard Gregory. He became interested in the way in which vision encodes the properties of the world around us, and spent periods studying this from a clinical perspective (at Tübingen University Eye Hospital) and in computer science (at the IBM UK Scientific Centre, Winchester). He moved to the Psychology Department at Bristol University in 1988, where he carried out a variety of projects on vision and complex scenes. In 2000 he became Professor of Psychology at the School of Cognitive and Computing Sciences at the University of Sussex. In 2002 he returned to Bristol University as Professor of Psychology and founded the Cognition and Information Technology Research Centre (COGNIT), which promotes interdisciplinary research spanning the cognitive, computing, and biological sciences. He currently holds grants from EPSRC, BBSRC, and industry, to investigate projects as diverse as the ecology of vision, the use of CCTV cameras in our cities, they safety of railway signals, and the construction of a self-aware robot. He is Executive Editor of the journal Perception.