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  Detecting Objects in Large Image Collections and Videos by Efficient Subimage Retrieval

Lampert, C. (2009). Detecting Objects in Large Image Collections and Videos by Efficient Subimage Retrieval. In Twelfth IEEE International Conference on Computer Vision (ICCV 2009) (pp. 987-994). Piscataway, NJ, USA: IEEE Computer Society.

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 Creators:
Lampert, CH1, 2, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: We study the task of detecting the occurrence of objects
in large image collections or in videos, a problem that combines
aspects of content based image retrieval and object
localization. While most previous approaches are either
limited to special kinds of queries, or do not scale to large
image sets, we propose a new method, efficient subimage
retrieval (ESR), which is at the same time very flexible and
very efficient. Relying on a two-layered branch-and-bound
setup, ESR performs object-based image retrieval in sets of
100,000 or more images within seconds. An extensive evaluation
on several datasets shows that ESR is not only very
fast, but it also achieves detection accuracies that are on
par with or superior to previously published methods for
object-based image retrieval.

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 Dates: 2009-10
 Publication Status: Published in print
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1109/ICCV.2009.5459359
BibTex Citekey: 6336
 Degree: -

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Title: Twelfth IEEE International Conference on Computer Vision (ICCV 2009)
Place of Event: Kyoto, Japan
Start-/End Date: 2009-09-29 - 2009-10-02

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Title: Twelfth IEEE International Conference on Computer Vision (ICCV 2009)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ, USA : IEEE Computer Society
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 987 - 994 Identifier: ISBN: 978-1-4244-4419-9