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An epipolar geometry-based approach for vision-based indoor localization

  • Harbin Institute of Technology

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

Abstract

Indoor positioning is getting more and more attention and research. We propose an epipolar geometry-based method for vision-based indoor localization using images. It needs an image collected in the positon that is aiming to localize. It uses SURF to pick up the feature points and filtrate them to remain good ones and get rid of bad ones. The good feature points are used to match the feature points in the database. (The feature points are selected by the images whose positions are already known). We use the matched feature points to calculate the essential matrix that include the translation information and rotary information. Then we can complete the localization by the relationship between the query image and the images in the database. What’s more we use the feature points to replace the images to build the database aiming to reduce the space and speed up the localization.

Original languageEnglish
Title of host publicationCommunications, Signal Processing, and Systems - Proceedings of the 2017 International Conference on Communications, Signal Processing, and Systems
EditorsQilian Liang, Min Jia, Jiasong Mu, Wei Wang, Xuhong Feng, Baoju Zhang
PublisherSpringer Verlag
Pages2643-2652
Number of pages10
ISBN (Print)9789811065705
DOIs
StatePublished - 2019
Event6th International Conference on Communications, Signal Processing, and Systems, CSPS 2017 - Harbin, China
Duration: 14 Jul 201716 Jul 2017

Publication series

NameLecture Notes in Electrical Engineering
Volume463
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference6th International Conference on Communications, Signal Processing, and Systems, CSPS 2017
Country/TerritoryChina
CityHarbin
Period14/07/1716/07/17

Keywords

  • Epipolar geometry
  • Essential matrix
  • Indoor localization
  • SURF

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