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The Role of Attention in Shaping Visual Perceptual Processes

  • John K. Tsotsos
  • Albert L. Rothenstein
Chapter
Part of the Springer Series in Cognitive and Neural Systems book series (SSCNS)

Abstract

It has been known now for over 20 years that an optimal solution to a basic vision problem such as visual search, which is robust enough to apply to any possible image or target, is unattainable because the problem of visual search is provably intractable (“Tsotsos, The complexity of perceptual search tasks, Proceedings of the International Joint Conference on Artificial Intelligence, 1989,” “Rensink, A new proof of the NP-completeness of visual match, Technical Report 89–22, University of British Columbia, 1989”). That the brain seems to solve it in an apparently effortless manner then poses a mystery. Either the brain is performing in a manner that cannot be captured computationally, or it is not solving that same generic visual search problem. The first option has been shown to not be the case (“Tsotsos and Bruce, Scholarpedia, 3(12), 6545, 2008”). As a result, this chapter will focus on the second possibility. There are two elements required to deal with this. The first is to show how the nature of the problem solved by the brain is fundamentally different from the generic one, and second to show how the brain might deal with those differences. The result is a biologically plausible and computationally well-founded account of how attentional mechanisms dynamically shape perceptual processes to achieve this seemingly effortless capacity that humans – and perhaps most seeing animals – possess.

Keywords

Visual Search Receptive Field Visual Search Task Computer Vision System Illusory Conjunction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Centre for Vision ResearchYork UniversityTorontoCanada

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