GRVS: a georeferenced video search engine

Authors:
Sakire Arslan Ay;Lingyan Zhang;Seon Ho Kim;Ma He;Roger Zimmermann
Affiliations:
University of Southern California, Los Angeles, CA, USA;National University of Singapore, Singapore, Singapore;University of the District of Columbia, Washington DC, DC, USA;National University of Singapore, Singapore, Singapore;National University of Singapore, Singapore, Singapore
Venue:
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Year:
2009

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Abstract

An increasing number of recorded videos are being tagged with geographic properties of the camera scenes. This meta-data is of significant use for storing, indexing and searching large collections of videos. By considering video related meta-information, more relevant and precisely delimited search results can be returned. Our system implementation demonstrates a prototype of a georeferenced video search engine (GRVS) that utilizes an estimation model of a camera's viewable scene for efficient video search. For video acquisition, our system provides an automated annotation software that captures videos and their respective field of views (FOV). The acquisition software allows community-driven data contributions to the search engine.