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A Network-Centric Epidemic Approach for Automated Image Label Annotation

  • Mehdy Bohlool
  • Ronaldo Menezes
  • Eraldo Ribeiro
Part of the Communications in Computer and Information Science book series (CCIS, volume 116)

Abstract

Automatically organizing and searching images by their content in large image datasets are major goals of Web-based search engines. Currently, these goals are accomplished by associating metadata information to each image in the database. In this paper, we investigate the use of network sciences to implement a metadata-propagation mechanism for images. We begin by creating a network of images connected by a part-based appearance-similarity measure, and propose an epidemiology-inspired model for metadata propagation. Our experiments show that organizing images as a network helps us label a large number images in the dataset in an economical way, i.e., with few manual metadata annotations.

Keywords

Average Path Length Label Propagation Sift Descriptor Image Network Uniform Propagation 
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 2011

Authors and Affiliations

  • Mehdy Bohlool
    • 1
  • Ronaldo Menezes
    • 1
  • Eraldo Ribeiro
    • 1
  1. 1.Florida Institute of TechnologyMelbourneUSA

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