• DocumentCode
    3281352
  • Title

    Multi-criteria search algorithm: An efficient approximate k-NN algorithm for image retrieval

  • Author

    Badr, Mario ; Vodislav, Dan ; Picard, David ; Shaoyi Yin ; Gosselin, Philippe-Henri

  • Author_Institution
    ENSEA, ETIS Univ. of Cergy-Pontoise, Cergy-Pontoise, France
  • fYear
    2013
  • fDate
    15-18 Sept. 2013
  • Firstpage
    2901
  • Lastpage
    2905
  • Abstract
    We propose a new method for approximate k-NN search in large scale image databases, based on top-k multi-criteria search techniques. The method defines a simple index structure based on sorted lists, which provides a good compromise between fast retrieval, storage requirements and update cost. The search algorithm delivers approximate results with guarantees about false negatives, with fast emergence of good approximations, monotonically improved and leading if necessary to an exact result. Experiments with the on-disk implementation show that our method produces very good approximate results several times faster than the Baseline method.
  • Keywords
    content-based retrieval; image retrieval; learning (artificial intelligence); search problems; sorting; visual databases; approximate k-NN search algorithm; baseline method; false negatives; fast retrieval; index structure; k nearest neighbors; large scale content based image retrieval; large scale image databases; multicriteria search algorithm; sorted lists; storage requirements; top-k multicriteria search techniques; update cost; CBIR; image databases; k-NN search; multi-criteria search; top-k algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2013 20th IEEE International Conference on
  • Conference_Location
    Melbourne, VIC
  • Type

    conf

  • DOI
    10.1109/ICIP.2013.6738597
  • Filename
    6738597