SPIRE: A Progressive Content-Based Spatial Image Retrieval Engine
Summary: Progressive, content-based SPIRE for multimodal unstructured data; supports image, image sequence, time series, and parametric data in large archives. Dynamic-programming–guided scheduling with hierarchical decorrelation enables progressive refinement on small data portions, yielding 20x+ speedups for template matching/classification and 400–800% for texture extraction, validated on solar flares and petroleum exploration. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Chung-Sheng Li (IBM)
- 2. Lawrence D. Bergman (IBM)
- 3. Yuan-Chi Chang (IBM)
- 4. Vittorio Castelli (IBM)
- 5. John R. Smith (IBM)
BibTeX Citation
@inproceedings{li_sigmod00,
title = {{SPIRE: A Progressive Content-Based Spatial Image Retrieval Engine}},
author = {Li, Chung-Sheng and Bergman, Lawrence D. and Chang, Yuan-Chi and Castelli, Vittorio and Smith, John R.},
series = {{SIGMOD} '00},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/342009.336583},
url = {https://dl.acm.org/doi/10.1145/342009.336583},
year = {2000}
}
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,352 | Boolean + Ranking: Querying a Database by K-Constrained Optimization | 2006 | SIGMOD | 5.6353412e-05 |
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