Change search
ReferencesLink to record
Permanent link

Direct link
Image matching using generalized scale-space interest points
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-9081-2170
2013 (English)In: Scale Space and Variational Methods in Computer Vision: 4th International Conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, , June 2-6, 2013, Proceedings / [ed] A. Kuijper et al, Springer Berlin/Heidelberg, 2013, Vol. 7893, 355-367 p.Conference paper (Refereed)
Abstract [en]

The performance of matching and object recognition methods based on interest points depends on both the properties of the underlying interest points and the associated image descriptors. This paper demonstrates the advantages of using generalized scale-space interest point detectors when computing image descriptors for image-based matching. These generalized scale-space interest points are based on linking of image features over scale and scale selection by weighted averaging along feature trajectories over scale and allow for a higher ratio of correct matches and a lower ratio of false matches compared to previously known interest point detectors within the same class. Specifically, it is shown how a significant increase in matching performance can be obtained in relation to the underlying interest point detectors in the SIFT and the SURF operators. We propose that these generalized scale-space interest points when accompanied by associated scale-invariant image descriptors should allow for better performance of interest point based methods for image-based matching, object recognition and related vision tasks.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2013. Vol. 7893, 355-367 p.
, Lecture Notes in Computer Science, ISSN 0302-9743
Keyword [en]
Feature detection, Interest point, Blob detection, Corner detection, Scale, Scale selection, Scale linking, Feature trajectory, Matching, Object recognition, Scale invariance, Affine invariance, Differential invariant, Image descriptor, Scale space, Computer vision
National Category
Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:kth:diva-118694DOI: 10.1007/978-3-642-38267-3_30ScopusID: 2-s2.0-84884406110OAI: diva2:607455
SSVM 2013: Fourth International Conference on Scale Space and Variational Methods in Computer Vision, June 2-6, 2013, Schloss Seggau, Graz region, Austria
Swedish Research Council, 2010-4766

QC 20130702

Available from: 2013-02-23 Created: 2013-02-23 Last updated: 2015-12-07Bibliographically approved

Open Access in DiVA

fulltext(8203 kB)341 downloads
File information
File name FULLTEXT01.pdfFile size 8203 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusThe final publication is available at

Search in DiVA

By author/editor
Lindeberg, Tony
By organisation
Computational Biology, CB
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 341 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 1455 hits
ReferencesLink to record
Permanent link

Direct link