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Cited by 847

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Statistics of natural image categories

Antonio B. Torralba, Aude Oliva·2003·Network Computation in Neural Systems
DOI 10.1088/0954-898x/14/3/302
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Abstract

In this paper we study the statistical properties of natural images belonging to different categories and their relevance for scene and object categorization tasks. We discuss how second-order statistics are correlated with image categories, scene scale and objects. We propose how scene categorization could be computed in a feedforward manner in order to provide top-down and contextual information very early in the visual processing chain. Results show how visual categorization based directly on low-level features, without grouping or segmentation stages, can benefit object localization and identification. We show how simple image statistics can be used to predict the presence and absence of objects in the scene before exploring the image.

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Metadata

Authors
Torralba, A. B., & Oliva, A.
Venue
Network Computation in Neural Systems
Publisher
Informa UK Limited
Published
2003-01
Volume
14
Issue
3
Pages
391-412
ISSN
  • 0954-898X (ISSN-L)
  • 1361-6536
DOI
10.1088/0954-898x/14/3/302
OpenAlex
W2113466552
Cited by
847
References
8
FWCI
25.86
Type
journal article
Language
en
Open access
closed

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Torralba, A. B., & Oliva, A. (2003). Statistics of natural image categories. Network Computation in Neural Systems. https://doi.org/10.1088/0954-898x/14/3/302

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