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Open AccessArticle

Movement-Oriented Objectified Organization and Retrieval Approach for Heterogeneous GeoVideo Data

National Engineering Research Center for E-Learning, Central China Normal University, Wuhan 430079, China
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
Laboratory for Environment Computation & Sustainability of Liaoning Province, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
School of Geodesy and Geomatics, Wuhan University, Wuhan 430072, China
Nuclear Industry Huzhou Engineering Investigation Institute, Huzhou 313000, China
Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA 22030, USA
School of Resource and Environment, University of Electric Science and Technology, Chengdu 611731, China
Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
Authors to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(7), 255;
Received: 20 April 2018 / Revised: 17 June 2018 / Accepted: 25 June 2018 / Published: 28 June 2018
PDF [6211 KB, uploaded 28 June 2018]


With the wide deployment of the video sensor network and the rapid development of video spatialization technology, the large volume of complex GeoVideo data necessitates improvements in the application efficiency of the GeoVideo database and GeoVideo surveillance system. Traditional storage management approaches focus on the optimization of access to the GeoVideo stream. However, they suffer from poor management of the diverse movement processes contained within it; for example, they cannot support associative queries or comprehensive analysis of multi-type GeoVideo data in complex geographic environments. This paper takes physical movement process in GeoVideo as a new type of object and carries out an objectified organization of the heterogeneous GeoVideo data around it (including the video stream, spatial references, interpretations of the video data, and the overall scene) in a Not only SQL-Structured Query Language (NoSQL-SQL) hybrid GeoVideo database. This paper systematically explores the hybrid spatiotemporal indexes and multi-modal retrieval methods around movement processes, which enrich the query modes of the GeoVideo data. A prototype implementation and experimental analysis are presented to prove the feasibility and effectiveness of this organization and retrieval approach. View Full-Text
Keywords: GeoVideo data; movement process; database organization; multi-modal retrieval GeoVideo data; movement process; database organization; multi-modal retrieval

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Wu, C.; Zhu, Q.; Zhang, Y.; Xie, X.; Qin, H.; Zhou, Y.; Zhang, P.; Yang, W. Movement-Oriented Objectified Organization and Retrieval Approach for Heterogeneous GeoVideo Data. ISPRS Int. J. Geo-Inf. 2018, 7, 255.

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