Geometric Hashing with Local Affine Frames


Chum, Ondřej, Matas, Jiří
CVPR, Los Alamitos, USA
Proc. of Conference on Computer Vision and Pattern Recognition (CVPR)
Volume 1, Pages 879-884
June, 2006

Abstract

We propose a novel representation of local image structure and a matching scheme that are insensitive to a wide range of appearance changes. The representation is a collection of local affine frames that are constructed on outer boundaries of maximally stable extremal regions (MSERs) in an affine-covariant way. Each local affine frame is described by a relative location of other local affine frames in its neighborhood. The image is thus represented by quantities that depend only on the location of the boundaries of MSERs. Inter-image correspondences between local affine frames are formed in constant time by geometric hashing. Direct detection of local affine frames removes the requirement of point-based hashing to establish reference frames in a combinatorial way, which has in the case of affine transform complexity that is cubic in the number of points. Local affine frames, which are also the quantities represented in the hash table, occupy a 6D space and hence data collisions are less likely compared with 2D point hashing. Experimentally, the robustness of the method and its insensitivity to photometric changes is demonstrated on images from different spectral bands of satellite sensor, on images of a transparent object and on images of an object taken during day and night.

Keywords

MSER, hashing, two-view matching, wide-baseline stereo

Full Paper

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Bibtex entry

@InProceedings{chum-hashing-cvpr06,
  author =      {Chum, Ond{\vr}ej and Matas, Ji{\vr}{\'i}},
  title =       {Geometric Hashing with Local Affine Frames},
  booktitle =   {Proc. of Conference on Computer Vision and 
                 Pattern Recognition (CVPR)},
  address =     {Los Alamitos, USA} ,
  year =        {2006},
  month =       {June},
  day =         {17--22},
  isbn        = {0-7695-2597-0},
  publisher   = {IEEE Computer Society},
  book_pages  = {1313},
  pages    =    {879--884},
  psurl    =    {[pdf]},
  annote = { We propose a novel representation of local image
    structure and a matching scheme that are insensitive to a wide
    range of appearance changes. The representation is a collection of
    local affine frames that are constructed on outer boundaries of
    maximally stable extremal regions (MSERs) in an affine-covariant
    way. Each local affine frame is de- scribed by a relative location
    of other local affine frames in its neighborhood. The image is
    thus represented by quan- tities that depend only on the location
    of the boundaries of MSERs. Inter-image correspondences between
    local affine frames are formed in constant time by geometric
    hashing. Direct detection of local affine frames removes the
    require- ment of point-based hashing to establish reference frames
    in a combinatorial way, which has in the case of affine trans-
    form complexity that is cubic in the number of points.  Local
    affine frames, which are also the quantities represented in the
    hash table, occupy a 6D space and hence data collisions are less
    likely compared with 2D point hashing. Experimentally, the
    robustness of the method and its in- sensitivity to photometric
    changes is demonstrated on im- ages from different spectral bands
    of satellite sensor, on images of a transparent object and on
    images of an object taken during day and night. },
  keywords =    {MSER, hashing, two-view matching, wide-baseline stereo},
  editor      = {Fitzgibbon, Andrew and Taylor, Camillo and LeCun , Yan},
  venue       = {New York ,  USA  },
  volume      = { 1 },
}