Linearity across spatial frequency in object recognition

Elizabeth S. Olds, Stephen A. Engel

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

In three experiments, we measured recognition as a function of exposure duration for three kinds of images of common objects: component images containing mainly low-spatial-frequency information, components containing mainly high-spatial-frequency information, and compound images created by summing the components. Our data were well fit by a model with a linear first stage in which the sums of the responses to the component images equalled the responses to the compound images. Our data were less well fit by a model in which the component responses combined by probability summation. These results support linear filler accounts of complex pattern recognition.

Original languageEnglish (US)
Pages (from-to)2109-2118
Number of pages10
JournalVision Research
Volume38
Issue number14
DOIs
StatePublished - Jul 1998
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by a Defense Department A.F.O.S.R. grant to EO. These experiments comprised part of EO’s Ph.D. dissertation, at Stanford University. We are grateful for helpful comments and assistance from Geoffrey Boynton, Christopher Furmanski, David Heeger, Geoffrey Loftus, David Rumelhart, Philip Servos, David Tolhurst, Brian Wandell, and Xuemei Zhang.

Copyright:
Copyright 2007 Elsevier B.V., All rights reserved.

Keywords

  • Animal
  • Human
  • Linear
  • Object
  • Recognition
  • Spatial frequency

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