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Rapid visual categorization is not guided by early salience-based selection.

Authors
  • Tsotsos, John K1
  • Kotseruba, Iuliia1
  • Wloka, Calden1
  • 1 Department of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada. , (Canada)
Type
Published Article
Journal
PLoS ONE
Publisher
Public Library of Science
Publication Date
Jan 01, 2019
Volume
14
Issue
10
Identifiers
DOI: 10.1371/journal.pone.0224306
PMID: 31648265
Source
Medline
Language
English
License
Unknown

Abstract

The current dominant visual processing paradigm in both human and machine research is the feedforward, layered hierarchy of neural-like processing elements. Within this paradigm, visual saliency is seen by many to have a specific role, namely that of early selection. Early selection is thought to enable very fast visual performance by limiting processing to only the most salient candidate portions of an image. This strategy has led to a plethora of saliency algorithms that have indeed improved processing time efficiency in machine algorithms, which in turn have strengthened the suggestion that human vision also employs a similar early selection strategy. However, at least one set of critical tests of this idea has never been performed with respect to the role of early selection in human vision. How would the best of the current saliency models perform on the stimuli used by experimentalists who first provided evidence for this visual processing paradigm? Would the algorithms really provide correct candidate sub-images to enable fast categorization on those same images? Do humans really need this early selection for their impressive performance? Here, we report on a new series of tests of these questions whose results suggest that it is quite unlikely that such an early selection process has any role in human rapid visual categorization.

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