| | |
Summary: Wavelet-based Salient Points with Scale Information for Classification
Alexandra Teynor and Hans Burkhardt
Department of Computer Science, Albert-Ludwigs-Universit¨at Freiburg, Germany
{teynor, Hans.Burkhardt}@informatik.uni-freiburg.de
Abstract
The calculation of local features at points of interest
is a vital part of many current image retrieval and ob-
ject detection systems. The wavelet-based interest point
detector by Loupias et al. was especially developed for
image retrieval applications. We show how the detector
can be extended by a Laplacian scale selection mech-
anism to provide scale information and compare it to
other state of the art detectors. The extended detector is
very well suited for visual object class recognition us-
ing feature cluster histograms. It discovers a variety of
image structures distributed over the entire image, and
the number of regions obtained can be adjusted easily.
These properties lead to superior performance, which
we confirmed by tests on a difficult animal categoriza-
tion problem.
|
