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SPIRE: a progressive content-based spatial image retrieval engine

Published: 16 May 2000 Publication History

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.

Cited By

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  • (2021)Multiple Exemplars Learning for Fast Image RetrievalProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482453(2455-2465)Online publication date: 26-Oct-2021
  • (2006)Boolean + rankingProceedings of the 2006 ACM SIGMOD international conference on Management of data10.1145/1142473.1142515(359-370)Online publication date: 27-Jun-2006
  • (2004)Human factors in color-based image retrieval: an empirical study on size estimate accuraciesJournal of Visual Communication and Image Representation10.1016/j.jvcir.2003.09.00115:2(113-131)Online publication date: Jun-2004

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  1. SPIRE: a progressive content-based spatial image retrieval engine

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      cover image ACM Conferences
      SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management of data
      May 2000
      604 pages
      ISBN:1581132174
      DOI:10.1145/342009
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 16 May 2000

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      Author Tags

      1. content-based retrieval
      2. digital library
      3. multimedia database

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      SIGMOD/PODS00
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      SIGMOD '00 Paper Acceptance Rate 42 of 248 submissions, 17%;
      Overall Acceptance Rate 785 of 4,003 submissions, 20%

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      Cited By

      View all
      • (2021)Multiple Exemplars Learning for Fast Image RetrievalProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482453(2455-2465)Online publication date: 26-Oct-2021
      • (2006)Boolean + rankingProceedings of the 2006 ACM SIGMOD international conference on Management of data10.1145/1142473.1142515(359-370)Online publication date: 27-Jun-2006
      • (2004)Human factors in color-based image retrieval: an empirical study on size estimate accuraciesJournal of Visual Communication and Image Representation10.1016/j.jvcir.2003.09.00115:2(113-131)Online publication date: Jun-2004

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