ABSTRACT: Change blindness, where observers have difficulty in perceiving changes between sequentially
presented images, and spatial pop put where regions of target textures need to be identified, are useful
tools to help explore human visual awareness. In this talk I will present results on work that blends a
computational model for image saliency and evolutionary optimization techniques to allow the automatic
custom generation of experimental stimuli. The results show that this computational approach is able to
predict observer performance in both special pop put and change blindness tasks.

BRIEF BIO: Peter is currently Professor of Computer Science and Director of Outreach in the School of
Electronic Engineering and Computer Science at Queen Mary, University of London. His research interests
are in visual perception, mathematical models for visual processing, cognitive science and biologically
inspired hardware and software. He has authored more than 90 papers in these areas. He recently served
on the Program Committee for ACII2009, CVPR 2009 and IEEE Artificial Life and is a member of the editorial
board of the Journal on Multimodal User Interfaces. Current research projects include LIREC, an EU FP7 IP,
developing long term synthetic companions, an EPSRC programme grant CHI+MED investigating design to reduce
human errors in medical software and an EPSRC PPE CS4fn, an outreach project to enthuse schools about 
computer science research. He was also elected a National Teaching Fellow by the Higher Education Academy in 2008.