Using top-points as interest points for image matching

Authors:
B. Platel;E. Balmachnova;L. M. J. Florack;F. M. W. Kanters;B. M. ter Haar Romeny
Affiliations:
Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Technische Universiteit Eindhoven, Eindhoven, The Netherlands
Venue:
DSSCV'05 Proceedings of the First international conference on Deep Structure, Singularities, and Computer Vision
Year:
2005

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Abstract

We consider the use of so-called 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. In a set of examples we show the excellent performance of top-points in an object retrieval task.