Detect Geographical Location by Multi-View Scene Matching

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

6 Scopus citations

Abstract

With the help of satellite geographical information, we present an innovative framework for localizing precisely while handling the varying views and different sources. We construct a convolutional neural network named Attentive Siamese-like Net (ASN) which can extract the multi-view scene representation. On top of it, a database retrieval system is established to search the realistic geographic coordinates quickly and reliably. For handling a complicated scene, a mass of visual data is collected from google satellite image and Google Earth Software. Experiments are carried out on two datasets of different scales and geographical range, which shows the superiority and effectiveness of our method.

Original languageEnglish
Title of host publication2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6467-6470
Number of pages4
ISBN (Electronic)9781728163741
DOIs
StatePublished - 26 Sep 2020
Event2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Virtual, Waikoloa, United States
Duration: 26 Sep 20202 Oct 2020

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Country/TerritoryUnited States
CityVirtual, Waikoloa
Period26/09/202/10/20

Keywords

  • multi-view scene
  • Satellite location
  • siamese network
  • visual-based Geo-Localization

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