• DocumentCode
    3708123
  • Title

    T-clustering: Image clustering by tensor decomposition

  • Author

    Amara Tariq;Hassan Foroosh

  • Author_Institution
    The Computational Imaging Lab., Computer Science, University of Central Florida, Orlando, FL, USA
  • fYear
    2015
  • Firstpage
    4803
  • Lastpage
    4807
  • Abstract
    Image clustering is an important tool for organizing evergrowing image repositories for efficient search and retrieval. A variety of clustering algorithms have been employed to cluster images. In this paper, we present a clustering algorithm, named T-Clustering, especially tailored to suit image collections. T-Clustering is based on tensor decomposition and takes into account the spatial configuration of images. This algorithm is non-parametric and works very well with raw images, thus alleviating the need for transformation of images in any feature domain. Our experiments prove that this algorithm outperforms well-known non-parametric clustering algorithms for a variety of image collections.
  • Keywords
    "Tensile stress","Clustering algorithms","Matrix decomposition","Image databases","Visualization","Yttrium","Manifolds"
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICIP.2015.7351719
  • Filename
    7351719