Kodak's consumer video benchmark data set: concept definition and annotation

  • Authors:

  • Alexander Loui;Jiebo Luo;Shih-Fu Chang;Dan Ellis;Wei Jiang;Lyndon Kennedy;Keansub Lee;Akira Yanagawa

  • Affiliations:

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

  • Venue:
  • Proceedings of the international workshop on Workshop on multimedia information retrieval
  • Year:
  • 2007

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Abstract

Semantic indexing of images and videos in the consumer domain has become a very important issue for both research and actual application. In this work we developed Kodak's consumer video benchmark data set, which includes (1) a significant number of videos from actual users, (2) a rich lexicon that accommodates consumers. needs, and (3) the annotation of a subset of concepts over the entire video data set. To the best of our knowledge, this is the first systematic work in the consumer domain aimed at the definition of a large lexicon, construction of a large benchmark data set, and annotation of videos in a rigorous fashion. Such effort will have significant impact by providing a sound foundation for developing and evaluating large-scale learning-based semantic indexing/annotation techniques in the consumer domain.