Think! Evidence

A global framework for scene gist

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dc.contributor Aude Oliva.
dc.contributor Massachusetts Institute of Technology. Dept. of Brain and Cognitive Sciences.
dc.contributor Massachusetts Institute of Technology. Dept. of Brain and Cognitive Sciences.
dc.creator Greene, Michelle R
dc.date 2010-04-28T17:11:03Z
dc.date 2010-04-28T17:11:03Z
dc.date 2009
dc.date 2009
dc.identifier http://hdl.handle.net/1721.1/54623
dc.identifier 601820808
dc.description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.
dc.description Cataloged from PDF version of thesis.
dc.description Includes bibliographical references.
dc.description Human observers are able to rapidly and accurately categorize natural scenes, but the representation mediating this feat is still unknown. Here we propose a framework of rapid scene categorization that does not segment a scene into objects and instead uses a vocabulary of global, ecological properties that describe spatial and functional aspects of scene space (such as navigability or mean depth). In Chapter 1, four experiments explore the human sensitivity to global properties for rapid scene categorization, as well as the computational sufficiency of these properties for predicting scene categories. Chapter 2 explores the time course of scene understanding, finding that global properties can be perceived with less image exposure than the computation of a scene's basic-level category. Finally, in Chapter 3, I explore aftereffects to adaptation to global properties, showing that repeated exposure to many global properties produces robust high-level aftereffects, thus providing evidence for the neural coding of these properties. Altogether, these results provide support for the hypothesis that rapid categorization of natural scenes may not be mediated primarily though objects and parts, but also through global properties of structure and affordance.
dc.description by Michelle R. Greene.
dc.description Ph.D.
dc.format 160 p.
dc.format application/pdf
dc.language eng
dc.publisher Massachusetts Institute of Technology
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
dc.rights http://dspace.mit.edu/handle/1721.1/7582
dc.subject Brain and Cognitive Sciences.
dc.title A global framework for scene gist
dc.type Thesis


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