Duplicate detection in consumer photography and news video

  • Authors:
  • Alejandro Jaimes;Shih-Fu Chang;Alexander C. Loui

  • Affiliations:
  • Columbia University, New York, NY;Columbia University, New York, NY;Eastman Kodak Company, Rochester, NY

  • Venue:
  • Proceedings of the tenth ACM international conference on Multimedia
  • Year:
  • 2002

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Abstract

Consumers often make more than one photograph of the same scene, creating non-identical duplicates and near duplicates. In Kodak's consumer photography database, on average, 19% of the images, per roll, fall into this category. Automatic detection of duplicates, therefore, is extremely useful in applications that help users organize their image collections. We introduce the challenging problem of non-identical duplicate image detection in consumer photography, describe STELLA (a novel interactive personal image collection organization system), and give an overview of our novel framework for detecting duplicate and near duplicate consumer photographs and news videos.