A visual object recognition system invariant to scale and rotation

Yasuomi D. Sato, Jenia Jitsev, Christoph Von Der Malsburg

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

4 Citations (Scopus)

Abstract

We here address the problem of scale and orientation invariant object recognition, making use of a correspondence-based mechanism, in which the identity of an object represented by sensory signals is determined by matching it to a representation stored in memory. The sensory representation is in general affected by various transformations, notably scale and rotation, thus giving rise to the fundamental problem of invariant object recognition. We focus here on a neurally plausible mechanism that deals simultaneously with identification of the object and detection of the transformation, both types of information being important for visual processing. Our mechanism is based on macrocolumnar units. These evaluate identity- and transformation-specific feature similarities, performing competitive computation on the alternatives of their own subtask, and cooperate to make a coherent global decision for the identity, scale and rotation of the object.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings
Pages991-1000
Number of pages10
EditionPART 1
DOIs
Publication statusPublished - 2008 Dec 1
Event18th International Conference on Artificial Neural Networks, ICANN 2008 - Prague, Czech Republic
Duration: 2008 Sep 32008 Sep 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5163 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Artificial Neural Networks, ICANN 2008
CountryCzech Republic
CityPrague
Period08/9/308/9/6

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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