Paper Info
Title
Smart Vidente: advances in mobile augmented reality for interactive visualization of underground infrastructure
Abstract
Many civil engineering tasks require to access geospatial data in the field and reference the stored information to the real-world situation. Augmented reality (AR), which interactively overlays 3D graphical content directly over a view of the world, can be a useful tool to visualize but also create, edit and update geospatial data representing real-world artifacts. We present research results on the next-generation field information system for companies relying on geospatial data, providing mobile workforces with capabilities for on-site inspection and planning, data capture and as-built surveying. To achieve this aim, we used mobile AR technology for on-site surveying of geometric and semantic attributes of geospatial 3D models on the user's handheld device. The interactive 3D visualizations automatically generated from production databases provide immediate visual feedback for many tasks and lead to a round-trip workflow where planned data are used as a basis for as-built surveying through manipulation of the planned data. Classically, surveying of geospatial objects is a typical scenario performed from utility companies on a daily basis. We demonstrate a mobile AR system that is capable of these operations and present first field trials with expert end users from utility companies. Our initial results show that the workflows of planning and surveying of geospatial objects benefit from our AR approach.
Year
DOI
Venue
2013
10.1007/s00779-012-0599-x
Personal and Ubiquitous Computing
Keywords
Field
DocType
as-built surveying,mobile ar technology,underground infrastructure,planned data,field trial,on-site surveying,smart vidente,interactive visualization,ar approach,geospatial data,geospatial object,utility company,mobile ar system,mobile augmented reality,surveying
Geospatial analysis,Information system,End user,Computer science,Augmented reality,Mobile device,Interactive visualization,Human–computer interaction,Automatic identification and data capture,Workflow,Multimedia
Journal
Volume
Issue
ISSN
17
7
1617-4917
Citations 
PageRank 
References 
20
0.92
16
Authors
3
Name
Order
Citations
PageRank
Gerhard Schall116911.20
Stefanie Zollmann222722.58
Gerhard Reitmayr3147395.20