Combining different types of scale space interest points using canonical sets

F.M.W. Kanters, T. Denton, A. Shokoufandeh, L.M.J. Florack, B.M. Haar Romenij, ter

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

2 Citations (Scopus)


Scale space interest points capture important photometric and deep structure information of an image. The information content of such points can be made explicit using image reconstruction. In this paper we will consider the problem of combining multiple types of interest points used for image reconstruction. It is shown that ordering the complete set of points by differential (quadratic) TV-norm (which works for single feature types) does not yield optimal results for combined point sets. The paper presents a method to solve this problem using canonical sets of scale space features. Qualitative and quantitative analysis show improved performance over simple ordering of points using the TV-norm.
Original languageEnglish
Title of host publicationProceedings of the First International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2007) 30 May - 2 June 2007, Ischia, Italy
EditorsF. Sgallari, A. Murli, N. Paragios
Place of PublicationBerlin, Germany
ISBN (Print)978-3-540-72822-1
Publication statusPublished - 2007
Eventconference; SSVM 2007, Ischia, Italy; 2007-05-30; 2007-06-02 -
Duration: 30 May 20072 Jun 2007

Publication series

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


Conferenceconference; SSVM 2007, Ischia, Italy; 2007-05-30; 2007-06-02
OtherSSVM 2007, Ischia, Italy

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