Ziyang Xiao, Dongxiang Zhang, Zepeng Li, Sai Wu, Kian-Lee Tan, Gang Chen
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DoveDB: A Declarative and Low-Latency Video Database
Concerning the usability and efficiency to manage video data generated from large-scale cameras, we demonstrate DoveDB, a declarative and low-latency video database. We devise a more comprehensive video query language called VMQL to improve the expressiveness of previous SQL-like languages, which are augmented with functionalities for model-oriented management and deployment. We also propose a light-weight ingestion scheme to extract tracklets of all the moving objects and build semantic indexes to facilitate efficient query processing. For user interaction, we construct a simulation environment with 120 cameras deployed in a road network and demonstrate three interesting scenarios. Using VMQL, users are allowed to 1) train a visual model using SQL-like statement and deploy it on dozens of target cameras simultaneously for online inference; 2) submit multi-object tracking (MOT) requests on target cameras, store the ingested results and build semantic indexes; and 3) issue an aggregation or top- k query on the ingested cameras and obtain the response within milliseconds. A preliminary video introduction of DoveDB is available at https://www.youtube.com/watch?v=N139dEyvAJk
期刊介绍:
The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.