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PATSI — Photo Annotation through Finding Similar Images with Multivariate Gaussian Models

  • Michal Stanek
  • Bartosz Broda
  • Halina Kwasnicka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6375)

Abstract

Automatic Image Annotation is important research topic in machine vision as it enables one to retrieve images from large databases by using textual queries. In recent years many machine learning techniques have been proposed to build detectors of concepts present on the images. In this paper we present a novel approach for image auto-annotation based on transfer of annotations from most similar images to the query image. We model image features by Multivariate Gaussian Distribution and measure distance between images by using Jensen-Shannon divergence. In spite of its simplicity, the proposed solution outperforms the state-of-the-art methods for image annotation and thus can be used as a baseline for developing other more elaborate methods.

Keywords

Query Image Similar Image Image Annotation Semantic Label Automatic Image Annotation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Michal Stanek
    • 1
  • Bartosz Broda
    • 1
  • Halina Kwasnicka
    • 1
  1. 1.Institute of InformaticsWrocław University of Technology 

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