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DoveDB: A Declarative and Low-Latency Video Database

Summary: DoveDB introduces VMQL, an expressive declarative video query language combining model-oriented training/deployment with lightweight ingestion that extracts tracklets and builds semantic indexes. Supports multi-camera model deployment, MOT ingestion, and millisecond aggregation/top-k queries in a 120-camera simulation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13225
Venue
VLDB
Year
2023
Pagerank
4.2856106e-05
Overall Rank
9,768 | 32.05%
DOI
10.14778/3611540.3611582

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Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1,388 MIRIS: Fast Object Track Queries in Video 2020 SIGMOD 0.00012260926
4,075 Visual Road: A Video Data Management Benchmark 2019 SIGMOD 6.4691764e-05
4,213 SVQ++: Querying for Object Interactions in Video Streams 2020 SIGMOD 6.3553296e-05
4,225 Vaas: Video Analytics At Scale 2020 VLDB 6.3469943e-05
4,865 OTIF: Efficient Tracker Pre-processing over Large Video Datasets 2022 SIGMOD 5.8684353e-05
8,247 Query-Driven Video Event Processing for the Internet of Multimedia Things 2021 VLDB 4.5511197e-05
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