GeoSearch: georeferenced video retrieval system

  • Authors:

  • Youngwoo Kim;Jinha Kim;Hwanjo Yu

  • Affiliations:

  • Pohang University of Science and Technology, Pohang, South Korea;Pohang University of Science and Technology, Pohang, South Korea;Pohang University of Science and Technology, Pohang, South Korea

  • Venue:
  • Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
  • Year:
  • 2012

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Abstract

Conventional video search systems, to find relevant videos, rely on textual data such as video titles, annotations, and text around the video. Nowadays, video recording devices such as ameras, smartphones and car blackboxes are equipped with GPS sensors and able to capture videos with spatiotemporal information such as time, location and camera direction. We call such videos georeferenced videos. This paper presents a georeferenced video retrieval system, geosearch, which efficiently retrieves videos containing a certain point or range in the map. To enable a fast search of georeferenced videos, geosearch adopts a novel data structure MBTR (Minimum Bounding Tilted Rectangle) in the leaf nodes of R-Tree. New algorithms are developed to build MBTRs from georeferenced videos and to efficiently process point and range queries on MBTRs. We demonstrate our system on real georeferenced videos, and show that, compared to previous methods, geosearch substantially reduces the index size and also improves the search speed for georeferenced video data. Our online demo is available at "http://dm.hwanjoyu.org/geosearch".