Dynamic link matching between feature columns for different scale and orientation

Yasuomi D. Sato, Christian Wolff, Philipp Wolfrum, Christoph Von Der Malsburg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Object recognition in the presence of changing scale and orientation requires mechanisms to deal with the corresponding feature transformations. Using Gabor wavelets as example, we approach this problem in a correspondence-based setting. We present a mechanism for finding feature-to-feature matches between corresponding points in pairs of images taken at different scale and/or orientation (leaving out for the moment the problem of simultaneously finding point correspondences). The mechanism is based on a macro-columnar cortical model and dynamic links. We present tests of the ability of finding the correct feature transformation in spite of added noise.

Original languageEnglish
Title of host publicationNeural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers
Pages385-394
Number of pages10
EditionPART 1
DOIs
Publication statusPublished - 2008 Oct 27
Event14th International Conference on Neural Information Processing, ICONIP 2007 - Kitakyushu, Japan
Duration: 2007 Nov 132007 Nov 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4984 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Conference on Neural Information Processing, ICONIP 2007
CountryJapan
CityKitakyushu
Period07/11/1307/11/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Sato, Y. D., Wolff, C., Wolfrum, P., & Von Der Malsburg, C. (2008). Dynamic link matching between feature columns for different scale and orientation. In Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers (PART 1 ed., pp. 385-394). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4984 LNCS, No. PART 1). https://doi.org/10.1007/978-3-540-69158-7_41