Top-points as interest points for image matching

Bram Platel, Evguenia Balmachnova, Luc Florack, Bart M. ter Haar Romeny

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

16 Citations (SciVal)
1 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationComputer Vision - ECCV 2006 (Proceedings 9th European Conference on Computer Vision, Graz, Austria, May 7-13, 2006)
EditorsH. Bischof, A. Leonardis, A. Pinz
PublisherSpringer
Pages418-429
Number of pages12
Volume1
ISBN (Print)3-540-33832-2
DOIs
Publication statusPublished - 2006

Publication series

NameLecture Notes in Computer Science
Volume3951
ISSN (Print)0302-9743

Fingerprint

Dive into the research topics of 'Top-points as interest points for image matching'. Together they form a unique fingerprint.

Cite this