Paper Info
Title
GeoSearch: georeferenced video retrieval system
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".
Year
DOI
Venue
2012
10.1145/2339530.2339775
KDD
Keywords
Field
DocType
conventional video search system,relevant video,videos georeferenced video,video recording device,real georeferenced video,georeferenced video,georeferenced video retrieval system,georeferenced video data,video title,retrieves video,indexation,georeferencing,data structure,spatial index,range query
Data structure,Video recording,Computer vision,Video retrieval,Information retrieval,Computer science,Range query (data structures),Georeference,Video tracking,Artificial intelligence,Global Positioning System,Bounding overwatch
Conference
Citations 
PageRank 
References 
3
0.37
17
Authors
3
Name
Order
Citations
PageRank
Youngwoo Kim170.77
Jin-ha Kim232918.78
Hwanjo Yu31715114.02