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Red Eye Detection through Bag-of-Keypoints Classification

  • Sebastiano Battiato
  • Mirko Guarnera
  • Tony Meccio
  • Giuseppe Messina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5716)

Abstract

Red eye artifacts are a well-known problem in digital photography. Small compact devices and point-and-click usage, typical of non-professional photography, greatly increase the likelihood for red eyes to appear in acquired images. Automatic detection of red eyes is a very challenging task, due to the variability of the phenomenon and the general difficulty in reliably discerning the shape of eyes.

This paper presents a method for discriminating between red eyes and other objects in a set of red eye candidates. The proposed method performs feature-based image analysis and classification just considering the bag-of-keypoints paradigm. Experiments involving different keypoint detectors/descriptors are performed. Achieved results are presented, as well as directions for future work.

Keywords

Red Eyes Feature Classification SIFT GLOH SVM 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sebastiano Battiato
    • 1
  • Mirko Guarnera
    • 2
  • Tony Meccio
    • 1
  • Giuseppe Messina
    • 2
  1. 1.Dipartimento di MatematicaUniversità degli Studi di CataniaCataniaItaly
  2. 2.Advanced System TechnologySTMicroelectronicsCataniaItaly

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