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STRG-Index: Spatio-Temporal Region Graph Indexing for Large Video Databases

Summary: STRG-Index models video with Spatio-Temporal Region Graphs capturing temporal relations; subgraph elimination reduces index size and search cost. Using EGED, STRG-Index with tree-based clustering yields faster, more accurate search than M-tree. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3741
Venue
SIGMOD
Year
2005
Pagerank
8.4572502e-05
Overall Rank
2,532 | 82.63%
DOI
10.1145/1066157.1066239

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{lee_sigmod05,
        title = {{STRG-Index: Spatio-Temporal Region Graph Indexing for Large Video Databases}},
        author = {Lee, JeongKyu and Oh, JungHwan and Hwang, Sae},
        series = {{SIGMOD} '05},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1066157.1066239},
        url = {https://dl.acm.org/doi/10.1145/1066157.1066239},
        year = {2005}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
56 M-tree: An Efficient Access Method for Similarity Search in Metric Spaces 1997 VLDB 0.00040719947
303 On The Marriage of Lp-norms and Edit Distance 2004 VLDB 0.00021956234
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