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  • Research Article
  • Open Access

Manifold-Ranking-Based Keyword Propagation for Image Retrieval

  • 1Email author,
  • 1,
  • 2,
  • 2,
  • 2 and
  • 1
EURASIP Journal on Advances in Signal Processing20062006:079412

https://doi.org/10.1155/ASP/2006/79412

  • Received: 30 August 2004
  • Accepted: 5 April 2005
  • Published:

Abstract

A novel keyword propagation method is proposed for image retrieval based on a recently developed manifold-ranking algorithm. In contrast to existing methods which train a binary classifier for each keyword, our keyword model is constructed in a straightforward manner by exploring the relationship among all images in the feature space in the learning stage. In relevance feedback, the feedback information can be naturally incorporated to refine the retrieval result by additional propagation processes. In order to speed up the convergence of the query concept, we adopt two active learning schemes to select images during relevance feedback. Furthermore, by means of keyword model update, the system can be self-improved constantly. The updating procedure can be performed online during relevance feedback without extra offline training. Systematic experiments on a general-purpose image database consisting of 5 000 Corel images validate the effectiveness of the proposed method.

Keywords

  • Feature Space
  • Propagation Process
  • Quantum Information
  • Image Retrieval
  • Additional Propagation

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Authors’ Affiliations

(1)
Department of Automation, Tsinghua University, Beijing, 100084, China
(2)
Microsoft Research Asia, 49 Zhichun Road, Beijing, 100080, China

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Copyright

© Tong et al. 2006

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