Combining different types of scale space interest points using canonical sets

Frans Kanters, Trip Denton, Ali Shokoufandeh, Luc Florack, Bart M. ter Haar Romeny

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

2 Citations (Scopus)

Abstract

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
PublisherSpringer
Pages374-385
Number of pages12
ISBN (Print)978-3-540-72822-1
DOIs
Publication statusPublished - 2007
EventFirst International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2007) - Ischia, Italy
Duration: 30 May 20072 Jun 2007

Publication series

NameLecture Notes in Computer Science
Volume4485
ISSN (Print)0302-9743

Conference

ConferenceFirst International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2007)
Country/TerritoryItaly
CityIschia
Period30/05/072/06/07

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