We consider the use of top-points for object retrieval. These points are based on scale-space and catastrophe theory, and are invariant under gray value scaling and offset as well as scale-Euclidean transformations. The differential properties and noise characteristics of these points are mathematically well understood. It is possible to retrieve the exact location of a top-point from any coarse estimation through a closed-form vector equation which only depends on local derivatives in the estimated point. All these properties make top-points highly suitable as anchor points for invariant matching schemes. By means of a set of repeatability experiments and receiver-operator-curves we demonstrate the performance of top-points and differential invariant features as image descriptors.
|Title of host publication||Computer Vision - ECCV 2006 (Proceedings 9th European Conference on Computer Vision, Graz, Austria, May 7-13, 2006), Part I|
|Editors||H. Bischof, A. Leonardis, A. Pinz|
|Publication status||Published - 2006|
|Name||Lecture Notes in Computer Science|