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Segmentation and Classification of Objects with Implicit Scene Context

  • Jan D. Wegner
  • Bodo Rosenhahn
  • Uwe Sörgel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7474)

Abstract

We present a novel approach to segment and classify objects in images into two classes. A binary conditional random field (CRF) framework is augmented with an unsupervised clustering step learning contextual relations of objects, the so-called implicit scene context (ISC). Several experiments with simulated data, images from benchmark data sets, and aerial images of an urban area show improved results compared to a standard CRF.

Keywords

segmentation classification conditional random field context clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jan D. Wegner
    • 1
  • Bodo Rosenhahn
    • 2
  • Uwe Sörgel
    • 1
  1. 1.Institute of Photogrammetry and GeoInformationGermany
  2. 2.Institut für InformationsverarbeitungLeibniz Universität HannoverGermany

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