Image Searching and Browsing by Active Aspect-Based Relevance Learning

  • Mark J. Huiskes
Conference paper

DOI: 10.1007/11788034_22

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4071)
Cite this paper as:
Huiskes M.J. (2006) Image Searching and Browsing by Active Aspect-Based Relevance Learning. In: Sundaram H., Naphade M., Smith J.R., Rui Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg

Abstract

Aspect-based relevance learning is a relevance feedback scheme based on a natural model of relevance in terms of image aspects. In this paper we propose a number of active learning and interaction strategies, capitalizing on the transparency of the aspect-based framework. Additionally, we demonstrate that, relative to other schemes, aspect-based relevance learning upholds its retrieval performance well under feedback consisting mainly of example images that are only partially relevant.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mark J. Huiskes
    • 1
  1. 1.Centre for Mathematics and Computer Science (CWI)AmsterdamThe Netherlands

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