AR city representation system based on map recognition using topological information

Hideaki Uchiyama, Hideo Saito, Myriam Servières, Guillaume Moreau

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

6 Citations (Scopus)

Abstract

This paper presents a system for overlaying 3D GIS data information such as 3D buildings onto a 2D physical urban map. We propose a map recognition framework by analysis of distribution of local intersections in order to recognize the area of the physical map from a whole map. The retrieval of the geographical area described by the physical map is based on a hashing scheme, which is called LLAH. In the results, we will show some applications augmenting additional information on the map.

Original languageEnglish
Title of host publicationVirtual and Mixed Reality - Third International Conference, VMR 2009, Held as Part of HCI International 2009, Proceedings
Pages128-135
Number of pages8
DOIs
Publication statusPublished - Dec 1 2009
Externally publishedYes
Event3rd International Conference on Virtual and Mixed Reality, VMR 2009. Held as Part of HCI International 2009 - San Diego, CA, United States
Duration: Jul 19 2009Jul 24 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5622 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Virtual and Mixed Reality, VMR 2009. Held as Part of HCI International 2009
CountryUnited States
CitySan Diego, CA
Period7/19/097/24/09

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Uchiyama, H., Saito, H., Servières, M., & Moreau, G. (2009). AR city representation system based on map recognition using topological information. In Virtual and Mixed Reality - Third International Conference, VMR 2009, Held as Part of HCI International 2009, Proceedings (pp. 128-135). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5622 LNCS). https://doi.org/10.1007/978-3-642-02771-0_15