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Estimating Shadows with the Bright Channel Cue

  • Alexandros Panagopoulos
  • Chaohui Wang
  • Dimitris Samaras
  • Nikos Paragios
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6554)

Abstract

In this paper, we introduce a simple but efficient cue for the extraction of shadows from a single color image, the bright channel cue. We discuss its limitations and offer two methods to refine the bright channel: by computing confidence values for the cast shadows, based on a shadow-dependent feature, such as hue; and by combining the bright channel with illumination invariant representations of the original image in a flexible way using an MRF model. We present qualitative and quantitative results for shadow detection, as well as results in illumination estimation from shadows. Our results show that our method achieves satisfying results despite the simplicity of the approach.

Keywords

Machine Intelligence Markov Random Field Color Channel Cast Shadow Shadow Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alexandros Panagopoulos
    • 1
  • Chaohui Wang
    • 2
    • 3
  • Dimitris Samaras
    • 1
  • Nikos Paragios
    • 2
    • 3
  1. 1.Image Analysis Lab, Computer Science Dept.Stony Brook UniversityUSA
  2. 2.Laboratoire MASÉcole Centrale ParisChâtenay-MalabryFrance
  3. 3.Equipe GALENINRIA Saclay - Île-de-FranceOrsayFrance

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