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Image annotation: which approach for realistic databases?

Published: 09 July 2007 Publication History

Abstract

This paper describes an efficient approach to image annotation. It ranked first on the recent scene categorization track of the ImagEVAL1 benchmark. We show how homogeneous global image descriptors combined with a pool of Support Vector Machines achieve very good results. We also used this approach on several well known object recognition databases to emphasize two main aspects of this research domain: the importance of contextual information in object recognition and the unsuitability of many standard databases for this task.

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cover image ACM Conferences
CIVR '07: Proceedings of the 6th ACM international conference on Image and video retrieval
July 2007
655 pages
ISBN:9781595937339
DOI:10.1145/1282280
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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Published: 09 July 2007

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Author Tags

  1. global descriptor
  2. image annotation
  3. object recognition
  4. scene categorization
  5. support vector machine

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