Merging storyboard strategies and automatic retrieval for improving interactive video search

  • Authors:

  • Michael G. Christel;Rong Yan

  • Affiliations:

  • Carnegie Mellon University, Pittsburgh, PA;IBM TJ Watson Research Center, Hawthorne, NY

  • Venue:
  • Proceedings of the 6th ACM international conference on Image and video retrieval
  • Year:
  • 2007

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Abstract

The Carnegie Mellon University Informedia group has enjoyed consistent success with TRECVID interactive search using traditional storyboard interfaces for shot-based retrieval. For TRECVID 2006 the output of automatic search was included for the first time with storyboards, both as an option for an interactive user and in a different run as the sole means of access. The automatic search makes use of relevance-based probabilistic retrieval models to determine weights for combining retrieval sources when addressing a given topic. Storyboard-based access using automatic search output outperformed extreme video retrieval interfaces of manual browsing with resizable pages and rapid serial visualization of keyframes that used the same output. Further, the full Informedia interface with automatic search results as an option along with other query mechanisms scored significantly better than all other TRECVID 2006 interactive search systems. Attributes of the automatic search and interactive search systems are discussed to further optimize shot-based retrieval from news corpora.