Exploring the synergy of humans and machines in extreme video retrieval

  • Authors:
  • Alexander G. Hauptmann;Wei-Hao Lin;Rong Yan;Jun Yang;Robert V. Baron;Ming-Yu Chen;Sean Gilroy;Michael D. Gordon

  • Affiliations:
  • School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

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.