@InProceedings{Hao-ICIP2003,
  IS = { zkontrolovano 12 Dec 2003 },
  UPDATE  = { 2003-12-12 },
  author =   {Shao, Hao and Svoboda, Tom{\'a}{\v s} and Ferrari,
                  Vittorio and Tuytelaars, Tinne and Van Gool, Luc},
  title =   {Fast indexing for image retrieval based on local
                  appearance with re-ranking},
  booktitle =   {IEEE International Conference on Image Processing},
  pages =        {4},
  year =   {2003},
  venue =   {Barcelona, Spain},
  month =   {September},
  day =     {14-17},
  publisher =   {IEEE Computer Society},
  address =   {Los Alamitos, USA},
  isbn =   {0-7803-7750-8},
  annote = { This paper describes an approach to retrieve images
    containing specific objects, scenes or buildings. The image
    content is captured by a set of local features. More precisely, we
    use so-called invariant regions. These are features with shapes
    that self-adapt to the viewpoint. The physical parts on the object
    surface that they carve out is the same in all views, even though
    the extraction proceeds from a single view only. The surface
    patterns within the regions are then characterized by a feature
    vector of moment invariants. Invariance is under affine geometric
    deformations and scaled color bands with an offset added. This
    allows regions from different views to be matched efficiently. An
    indexing technique based on Vantage Point Tree organizes the
    feature vectors in such a way that a naive sequential search can
    be avoided. This results in sublinear computation times to
    retrieve images from a database. In order to get sufficient
    certainty about the correctness of the retrieved images, a method
    to increase the number of matched regions is introduced. This way,
    the system is both efficient and discriminant. It is demonstrated
    how scenes or buildings are recognized, even in case of partial
    visibility and under a large variety of viewing condition
    changes.},
  keywords =   {Local based image recognition, appearance based recoginiton,
                  database indexing, feature based recognition},
  note = {CD-ROM},
}