id: 06018889
dt: j
an: 06018889
au: Strong, Grant; Gong, Minglun
ti: Similarity-based image organization and browsing using multi-resolution
    self-organizing map.
so: Image Vis. Comput. 29, No. 11, 774-786 (2011).
py: 2011
pu: Elsevier, Amsterdam
la: EN
cc: 
ut: similarity-based image browsing; self-organizing map; general computing on
    GPU
ci: 
li: doi:10.1016/j.imavis.2011.08.007
ab: Summary: An algorithm is presented in this paper to facilitate the
    exploration of large image collections based on visual similarities.
    Starting with an unordered and unannotated set of images, the algorithm
    first extracts the salient details into feature vectors using both
    color and gradient information. The feature vectors are then used to
    train a self-organizing map which maps high-dimensional feature vectors
    onto a 2D canvas so that images with similar feature vectors are
    grouped together. When users browse the image collection, an image
    collage is generated that selects and displays the most pertinent set
    of images based on which portion of the 2D canvas is currently in view.
    Flowing from an overview to details is a seamless operation controlled
    simply by pan and zoom, with representative images selected in a
    consistent and predictable way. To make organizing larger image
    collections practical in interactive time, the organization algorithm
    is designed to run in parallel on graphics processing units. Overall
    this paper presents an end-to-end solution that facilitates the surfing
    of image collections in a fresh way.
rv: