Design and implementation of geo-tagged video search framework

  • Authors:

  • Seon Ho Kim;Sakire Arslan Ay;Roger Zimmermann

  • Affiliations:

  • University of Southern California, Los Angeles, CA 90089, USA;University of Southern California, Los Angeles, CA 90089, USA;National University of Singapore, Singapore 117417, Singapore

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2010

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Abstract

User generated video content is experiencing significant growth which is expected to continue and further accelerate. As an example, users are currently uploading 20h of video per minute to YouTube. Making such video archives effectively searchable is one of the most critical challenges of multimedia management. Current search techniques that utilize signal-level content extraction from video struggle to scale. Here we present a framework based on the complementary idea of acquiring sensor streams automatically in conjunction with video content. Of special interest are geographic properties of mobile videos. The meta-data from sensors can be used to model the coverage area of scenes as spatial objects such that videos can effectively, and on a large scale, be organized, indexed and searched based on their field-of-views. We present an overall framework that is augmented with our design and implementation ideas to illustrate the feasibility of this concept of managing geo-tagged video.