June 2006
Volume 6, Issue 6
Free
Vision Sciences Society Annual Meeting Abstract  |   June 2006
Seeing the {closed+camouflage+natural=forest} for the trees: Rapid scene categorization can be mediated by conjunctions of global scene properties
Author Affiliations
  • Michelle R. Greene
    Massachusetts Institute of Technology, Department of Brain and Cognitive Science
  • Aude Oliva
    Massachusetts Institute of Technology, Department of Brain and Cognitive Science
Journal of Vision June 2006, Vol.6, 462. doi:10.1167/6.6.462
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      Michelle R. Greene, Aude Oliva; Seeing the {closed+camouflage+natural=forest} for the trees: Rapid scene categorization can be mediated by conjunctions of global scene properties. Journal of Vision 2006;6(6):462. doi: 10.1167/6.6.462.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

The human ability to categorize novel natural scenes with minimal exposure duration is a truly remarkable and mysterious feat. How is the initial scene representation constructed to allow for rapid scene categorization given the many possible levels of scene description (objects, global layout and functional properties, semantic categories, etc.)? In the first experiment, we tested the temporal availability of seven global scene properties (e.g. volume, navigability, openness) relative to semantic categorization of eight common natural scene categories (e.g. forest, lake) by comparing presentation-time thresholds for these tasks. Results showed that, for the same images, global properties were available for report with less exposure time (25 msec) than semantic categories (43 msec). Do combinations of global scene properties predict semantic categorization? In a second experiment, we compared human performances on a rapid scene categorization task to a model observer whose input was the global property descriptors for each image. The model was trained on the distributions of scene categories along global property dimensions, outputting the scene category with the maximum likelihood summed over global properties. Remarkably, the model's categorization performance matched human performance for presentation times of 30 msec (74% vs. 70% correct) as well as the patterns of availability for individual categories. Furthermore, errors made by the model observer predicted human errors for 69% of images. Taken together, these results strongly suggest that the rapid semantic categorization of natural scenes by humans can be mediated by detecting conjunctions of global scenes properties.

Greene, M. R. Oliva, A. (2006). Seeing the {closed+camouflage+natural=forest} for the trees: Rapid scene categorization can be mediated by conjunctions of global scene properties [Abstract]. Journal of Vision, 6(6):462, 462a, http://journalofvision.org/6/6/462/, doi:10.1167/6.6.462. [CrossRef]
Footnotes
 MG supported by NSF GRF
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