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Exploring the Synergy of Humans and Machines in Extreme Video Retrieval

  • Alexander G. Hauptmann
  • Wei-Hao Lin
  • Rong Yan
  • Jun Yang
  • Robert V. Baron
  • Ming-Yu Chen
  • Sean Gilroy
  • Michael D. Gordon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4071)

Abstract

We introduce an interface for efficient video search that exploits the human ability to quickly scan visual content, after automatic retrieval has arrange the images in expected order of relevance. While extreme video retrieval is taxing to the human, it is also extremely effective. Two variants of extreme retrieval are demonstrated, 1) RSVP which automatically pages through images with user-control of the paging speed, while the user marks relevant shots and 2) MBRP where the user manually controls paging and adjusts the number of images per page, depending on the density of relevant shots.

Keywords

Average Precision Rapid Serial Visual Presentation Mean Average Precision Relevant Image Video Retrieval 
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 2006

Authors and Affiliations

  • Alexander G. Hauptmann
    • 1
  • Wei-Hao Lin
    • 1
  • Rong Yan
    • 1
  • Jun Yang
    • 1
  • Robert V. Baron
    • 1
  • Ming-Yu Chen
    • 1
  • Sean Gilroy
    • 1
  • Michael D. Gordon
    • 1
  1. 1.School of Computer ScienceCarnegie Mellon UniversityPittsburghUSA

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