The perception of good and bad natural scene category exemplars

Caddigan, Eamon

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https://hdl.handle.net/2142/34466 Copy

Description

Title

The perception of good and bad natural scene category exemplars

Author(s)

Caddigan, Eamon

Issue Date

2012-09-18T21:18:30Z

Director of Research (if dissertation) or Advisor (if thesis)

Beck, Diane M.

Doctoral Committee Chair(s)

Beck, Diane M.

Committee Member(s)

• Li, Fei-Fei
• Simons, Daniel J.
• Hummel, John E.
• Lleras, Alejandro

Department of Study

Psychology

Discipline

Psychology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

Scene Perception

Abstract

Images of natural scenes are easily categorized by human observers. Recent work has shown that “good” images, or those that are more representative of their category, are more easily categorized than “bad” ones. The present research investigates a novel hypothesis: that “good” images of scenes are more easily perceived than bad images. Participants performed a two-alternative forced choice task in which they indicated whether an image was an intact or phase-scrambled scene photograph. In this task, observers were able to “see” good images better than bad scenes, more accurately detecting their brief presentations. This effect is not influenced by prior knowledge about the categories used in the experiment. Scene inversion is also shown to have a similar effect on the intact/scrambled discrimination effect, but it does not interact with category representativeness, indicating that the advantage conferred by good exemplars is invariant to inversion. Finally, the good and bad images were analyzed using an objective estimate of image typicality, and this factor was also shown to predict observers' ability to detect the images. These results document a close relationship between natural scene categorization and detection, suggesting that rapid scene perception is strongly influenced by our experience with typical and representative environments.

Graduation Semester

2012-08

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http://hdl.handle.net/2142/34466

Copyright and License Information

Copyright 2012 Eamon Caddigan

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