Robot navigation by panoramic vision and attention guided features

  • Alexandre Bur
  • , Adriana Tapus
  • , Nabil Ouerhani
  • , Roland Siegwart
  • , Heinz Hügli

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

Abstract

In visual-based robot navigation, panoramic vision emerges as a very attractive candidate for solving the localization task. Unfortunately, current systems rely on specific feature selection processes that do not cover the requirements of general purpose robots. In order to fulfill new requirements of robot versatility and robustness to environmental changes, we propose in this paper to perform the feature selection of a panoramic vision system by means of the saliency-based model of visual attention, a model known for its universality. The first part of the paper describes a localization system combining panoramic vision and visual attention. The second part presents a series of indoor localization experiments using panoramic vision and attention guided feature detection. The results show the feasibility of the approach and illustrate some of its capabilities.

Original languageEnglish
Title of host publicationProceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages695-698
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2006
Externally publishedYes
Event18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
Duration: 20 Aug 200624 Aug 2006

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume1
ISSN (Print)1051-4651

Conference

Conference18th International Conference on Pattern Recognition, ICPR 2006
Country/TerritoryChina
CityHong Kong
Period20/08/0624/08/06

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