Classification of High-Dimension PDFs Using the Hungarian Algorithm

  • James S. Cope
  • Paolo Remagnino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7626)


The Hungarian algorithm can be used to calculate the earth mover’s distance, as a measure of the difference between two probability density functions, when the pdfs are described by sets of n points sampled from their distributions. However, information generated by the algorithm about precisely how the pdfs are different is not utilized. In this paper, a method is presented that incorporates this information into a ‘bag-of-words’ type method, in order to increase the robustness of a classification. This method is applied to an image classification problem, and is found to outperform several existing methods.


Probability Density Function Feature Space Image Retrieval Transportation Problem Class Object 
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 2012

Authors and Affiliations

  • James S. Cope
    • 1
  • Paolo Remagnino
    • 1
  1. 1.Digital Imaging Research CentreKingston UniversityLondonUK

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