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Scene-Centered Description from Spatial Envelope Properties

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Book cover Biologically Motivated Computer Vision (BMCV 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2525))

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Abstract

In this paper, we propose a scene-centered representation able to provide a meaningful description of real world images at multiple levels of categorization (from superordinate to subordinate levels). The scene-centered representation is based upon the estimation of spatial envelope properties describing the shape of a scene (e.g. size, perspective, mean depth) and the nature of its content. The approach is holistic and free of segmentation phase, grouping mechanisms, 3D construction and object-centered analysis.

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Author information

Authors and Affiliations

  1. Department of Psychology and Cognitive Science Program, Michigan State University, 48824, East Lansing, MI, USA

    Aude Oliva

  2. Artificial Intelligence Laboratory, MIT, 02139, Cambridge, MA, USA

    Antonio Torralba

Authors
  1. Aude Oliva
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  2. Antonio Torralba
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Editor information

Editors and Affiliations

  1. Max Planck Institute for Biological Cybernetics, Spemannstraße 38, 72076, Tübingen, Germany

    Heinrich H. Bülthoff  & Christian Wallraven  & 

  2. Department of Computer Science and Engineering, Korea University, Anam-dong, Seongbuk-ku, 136-701, Seoul, Korea

    Seong-Whan Lee

  3. Department of Brain and Cognitive Sciences, Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 45 Carleton Street, 02142, Cambridge, MA, USA

    Tomaso A. Poggio

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© 2002 Springer-Verlag Berlin Heidelberg

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Oliva, A., Torralba, A. (2002). Scene-Centered Description from Spatial Envelope Properties. In: Bülthoff, H.H., Wallraven, C., Lee, SW., Poggio, T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36181-2_26

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  • DOI: https://doi.org/10.1007/3-540-36181-2_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00174-4

  • Online ISBN: 978-3-540-36181-7

  • eBook Packages: Springer Book Archive

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