Optimizing multidimensional index trees for main memory access
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Efficient Evaluation of Continuous Range Queries on Moving Objects
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Q+Rtree: Efficient Indexing for Moving Object Databases
DASFAA '03 Proceedings of the Eighth International Conference on Database Systems for Advanced Applications
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Spatial indexing in microsoft SQL server 2008
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
Fast forensic video event retrieval using geospatial computing
Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application
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With more and more live sensors being added to geospatial applications, huge amount of sensor data are generated and saved in spatial database. Managing and mining these large-scale ever-changing data becomes new challenges for geospatial studies. In this paper, we present an application-oriented case study to show how to retrieve target tracking data from big dataset saved in spatial database. Our video event retrieval system collects thirty days (8790 GB) high definition video data from six surveillance cameras, analyze them and extract roughly ten million video target tracks. These tracks are projected onto world coordinates and pumped into a spatial database. The system performance of inserting and retrieving these tracks is analyzed in terms of spatial data type design, spatial index configuration, online operation capacity, query optimization and scalability handling. Our insights of saving, managing and retrieving target tracks in a large-scale are presented.