SPIRE: A Progressive Content-Based Spatial Image Retrieval Engine Chung-Sheng Li, Lawrence D. Bergman, Vittorio Castelli, and John R. Smith   View Demo (HTML)   Return to Demonstrations Abstract In this demo, we will show the implementation of a content-based SPatial Image Retrieval Engine (SPIRE) for multimodal unstructured data. This architecture provides a framework for retrieving multi-modal data including image, image sequence, time series and parametric data from large archives. Dramatic speedup (from a factor of 4 to 35) has been achieved for many search operations such as template matching, texture feature extraction. This framework has been applied and validated in solar flares and petroleum exploration in which spatial and spatial-temporal phenomena are located. BIBTEX @inproceedings{DBLP:conf/sigmod/LiBCS00,   author    = {Chung-Sheng Li and                 Lawrence D. Bergman and                 Vittorio Castelli and                 John R. Smith},    editor    = {Weidong Chen and                 Jeffrey F. Naughton and                 Philip A. Bernstein},    title     = {SPIRE: A Progressive Content-Based Spatial Image Retrieval Engine},    booktitle = {Proceedings of the 2000 ACM SIGMOD International Conference on                 Management of Data, May 16-18, 2000, Dallas, Texas, USA},    journal   = {SIGMOD Record},    publisher = {ACM},    volume    = {29},    number    = {2},    year      = {2000},    isbn      = {1-58113-218-2},    pages     = {598},    crossref  = {DBLP:conf/sigmod/2000},    bibsource = {DBLP, http://dblp.uni-trier.de} } }, DiSC'01 Copyright ©2002 ACM Inc.