Abstract 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.
Top-Points as Interest Points for Image Matching
Computer Vision – ECCV 2006 ; 3 ; 418-429
Lecture Notes in Computer Science ; 3951 , 3
2006-01-01
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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