Clipboard: a visual search and browsing engine for tablet and PC

  • Authors:
  • David Scott;Jinlin Guo;Hongyi Wang;Yang Yang;Frank Hopfgartner;Cathal Gurrin

  • Affiliations:
  • Dublin City University, Dublin, Ireland;Dublin City University, Dublin, Ireland;Dublin City University, Dublin, Ireland;Dublin City University, Dublin, Ireland;Dublin City University, Dublin, Ireland;Dublin City University, Dublin, Ireland

  • Venue:
  • MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
  • Year:
  • 2012

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Abstract

In this work, we present a handheld video browser that utilizes two methods of search; Concept Search and Keyframe Similarity. Concept Search allows a user to define a query using selected visual concepts and presents the user with a cluster of video segments based on extracted image features using OpponentSIFT. Keyframe Similarity has a dependance on the previous search for input criteria, allowing a user to select a keyframe for similarity search, returning three types of results; local keyframes from the current scene, global shot similarity based on visual features and text similarity of shots, based on frequently occurring words generated from ASR transcripts.