Size tuning in the absence of spatial frequency tuning in object recognition

József Fiser, Suresh Subramaniam, Irving Biederman

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

How do we attend to objects at a variety of sizes as we view our visual world? Because of an advantage in identification of lowpass over highpass filtered patterns, as well as large over small images, a number of theorists have assumed that size-independent recognition is achieved by spatial frequency (SF) based coarse-to-fine tuning. We found that the advantage of large sizes or low SFs was lost when participants attempted to identify a target object (specified verbally) somewhere in the middle of a sequence of 40 images of objects, each shown for only 72 ms, as long as the target and distractors were the same size or spatial frequency (unfiltered or low or high bandpassed). When targets were of a different size or scale than the distractors, a marked advantage (pop out) was observed for large (unfiltered) and low SF targets against small (unfiltered) and high SF distractors, respectively, and a marked decrement for the complementary conditions. Importantly, this pattern of results for large and small images was unaffected by holding absolute or relative SF content constant over the different sizes and it could not be explained by simple luminance- or contrast-based pattern masking. These results suggest that size/scale tuning in object recognition was accomplished over the first several images ( < 576 ms) in the sequence and that the size tuning was implemented by a mechanism sensitive to spatial extent rather than to variations in spatial frequency.

Original languageEnglish
Pages (from-to)1931-1950
Number of pages20
JournalVision Research
Volume41
Issue number15
DOIs
Publication statusPublished - Jun 26 2001

Keywords

  • Coarse-to-fine tuning
  • Human object recognition
  • Rapid serial visual presentation
  • Size invariance
  • Spatial frequency

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems

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