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

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