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G. M. Wallis and H. H. B{\"{u}}lthoff
ABSTRACT
As viewing distance, viewing angle or lighting conditions change, so too does the image of an object which we see. Despite the seemingly endless variety of images that objects can project, the human visual system remains able to rapidly and reliably identify them across huge changes in appearance. Understanding how humans achieve this feat of recognition has long been a source of debate. Despite a concerted e ort, researchers are still undecided even about the most fundamental questions of how objects are represented in cortex. This chapter gives a brief overview of some theoretical approaches in the context of mainly neurophysiological evidence. It also considers the related question of objects within a physical context, that is the analysis of visual scenes. Scene analysis is relevant to the question of object recognition because scenes are initially recognised at a holistic, object-like level, providing a context or `gist' which itself in uences the speed and accuracy of recognition of the constituent objects (Rensink, 2000). A precise characterisation of gist remains elusive, but it may well include information such as global color patterns, spatial frequency content, correlational structure, anything which is useful for categorising or recognising the scene. 
ECVision indexed and annotated bibliography of cognitive computer vision publications
This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1
The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
The Handbook of Brain Theory and Neural NetworksSite generated on Friday, 06 January 2006