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Published January 31, 2007 | Published
Journal Article Open

What do we perceive in a glance of a real-world scene?

Abstract

What do we see when we glance at a natural scene and how does it change as the glance becomes longer? We asked naive subjects to report in a free-form format what they saw when looking at briefly presented real-life photographs. Our subjects received no specific information as to the content of each stimulus. Thus, our paradigm differs from previous studies where subjects were cued before a picture was presented and/or were probed with multiple-choice questions. In the first stage, 90 novel grayscale photographs were foveally shown to a group of 22 native-English-speaking subjects. The presentation time was chosen at random from a set of seven possible times (from 27 to 500 ms). A perceptual mask followed each photograph immediately. After each presentation, subjects reported what they had just seen as completely and truthfully as possible. In the second stage, another group of naive individuals was instructed to score each of the descriptions produced by the subjects in the first stage. Individual scores were assigned to more than a hundred different attributes. We show that within a single glance, much object- and scene-level information is perceived by human subjects. The richness of our perception, though, seems asymmetrical. Subjects tend to have a propensity toward perceiving natural scenes as being outdoor rather than indoor. The reporting of sensory- or feature-level information of a scene (such as shading and shape) consistently precedes the reporting of the semantic-level information. But once subjects recognize more semantic-level components of a scene, there is little evidence suggesting any bias toward either scene-level or object-level recognition.

Additional Information

© 2007 ARVO. Received December 30, 2005; published January 31, 2007. This work was supported by an NSF ERC grant from Caltech. L. F.-F. was supported by Paul and Daisy Soros Fellowship for New Americans as well as an NSF Graduate Fellowship. The authors thank Irv Biederman, Jochen Brown, Shin Shimojo, Dan Simons, Rufin VanRullen and three anonymous reviewers for their helpful comments. L. F.-F. and A. I. contributed equally in this work. Commercial relationships: none.

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August 22, 2023
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