Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Occlusion in outdoor Augmented Reality using geospatial building data
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.ORCID iD: 0000-0002-3017-3813
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).ORCID iD: 0000-0003-4616-189X
2017 (English)In: VRST '17 Proceedings of the 23rd ACM Symposium on Virtual Reality Software and Technology, Association for Computing Machinery (ACM), 2017, Vol. Part F131944, article id a30Conference paper (Refereed)
Abstract [en]

Aligning virtual and real objects in Augmented Reality (AR) is essential for the user experience. Without alignment, the user loses suspension of disbelief and the sense of depth, distance, and size. Occlusion is a key feature to be aligned. Virtual content should be partially or fully occluded if real world objects are in its line-of-sight. The challenge for simulating occlusion is to construct the geometric model of the environment. Earlier studies have aimed to create realistic occlusions, yet most have either required depth-sensing hardware or a static predened environment. is paper proposes and evaluates an alternative model-based method for dynamic outdoor AR of virtual buildings rendered on non depth-sensing smartphones. It uses geospatial data to construct the geometric model of real buildings surrounding the virtual building. The method removes the target regions from the virtual building using masks constructed from real buildings. While the method is not pixel-perfect, meaning that the simulated occlusion is not fully realistic, results from the user study indicate that it fullled its goal. A majority of the participants expressed that their experience and depth perception improved with the method activated. The result from this study has applications to mobile AR since the majority of smartphones are not equipped with depth sensors. Using geospatial data for simulating occlusions is a suciently eective solution until depth-sensing AR devices are more widely available.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2017. Vol. Part F131944, article id a30
Series
Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST
Keyword [en]
AR, Augmented Reality, Geospatial data, Occlusion, Open Street Maps, Physical simulation
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-220740DOI: 10.1145/3139131.3139159Scopus ID: 2-s2.0-85038585895ISBN: 9781450355483 (print)OAI: oai:DiVA.org:kth-220740DiVA, id: diva2:1172127
Conference
23rd ACM Conference on Virtual Reality Software and Technology, VRST 2017, 8 November 2017 through 10 November 2017
Note

QC 20180109

Available from: 2018-01-09 Created: 2018-01-09 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Picha Edwardsson, MalinRomero, Mario

Search in DiVA

By author/editor
Kasperi, JohanPicha Edwardsson, MalinRomero, Mario
By organisation
School of Computer Science and Communication (CSC)Media Technology and Interaction Design, MIDComputational Science and Technology (CST)
Other Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 29 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf