Robust Color Contour Object Detection Invariant to Shadows

  • Jorge Scandaliaris
  • Michael Villamizar
  • Juan Andrade-Cetto
  • Alberto Sanfeliu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4756)

Abstract

In this work a new robust color and contour based object detection method in images with varying shadows is presented. The method relies on a physics-based contour detector that emphasizes material changes and a contour-based boosted classifier. The method has been tested in a sequence of outdoor color images presenting varying shadows using two classifiers, one that learnt contour object features from a simple gradient detector, and another that learnt from the photometric invariant contour detector. It is shown that the detection performance of the classifier trained with the photometric invariant detector is significantly higher than that of the classifier trained with gradient detector.

Keywords

color invariance shadow removal object detection boosting 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jorge Scandaliaris
    • 1
  • Michael Villamizar
    • 1
  • Juan Andrade-Cetto
    • 1
  • Alberto Sanfeliu
    • 1
    • 2
  1. 1.Institut de Robòtica i Informàtica Industrial (UPC-CSIC) 
  2. 2.Dept. System Engineering and Automation, Universitat Politècnica de Catalunya (UPC) BarcelonaSpain

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