A comparative study of image feature detection and description methods for robot vision

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

Abstract

Detection and description of local features in images is an essential task in robot vision. This task allows to identify and uniquely specify stable and invariant regions in a observed scene. Many successful detectors and descriptors have been proposed. However, the proper combination of a detector and a descriptor is not trivial because there is a trade-off among different performance criteria. This work presents a comparative study of successful image feature detection and description methods in the context of the simultaneous localization and mapping problem. The considered methods are exhaustively evaluated in terms of accuracy, robustness, and processing time.

Original languageEnglish
Title of host publicationOptics and Photonics for Information Processing XIII
EditorsKhan M. Iftekharuddin, Abdul A. S. Awwal, Victor H. Diaz-Ramirez, Andres Marquez
PublisherSPIE
ISBN (Electronic)9781510629653
DOIs
StatePublished - 2019
EventOptics and Photonics for Information Processing XIII 2019 - San Diego, United States
Duration: 13 Aug 201914 Aug 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11136
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceOptics and Photonics for Information Processing XIII 2019
Country/TerritoryUnited States
CitySan Diego
Period13/08/1914/08/19

Keywords

  • Image matching
  • Local feature descriptor
  • Local feature detector
  • Simultaneous Localization and Mapping

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