Automation and visualization in geographic immersive virtual environments
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Automation and Visualization in Geographic Immersive Virtual Environments. Thomas J. Pingel , Northern Illinois University Keith C. Clarke, University of California Santa Barbara AutoCarto 2012 International Research Symposium September 16-20, 2012 Columbus, Ohio.

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Automation and visualization in geographic immersive virtual environments

Automation and Visualization in Geographic Immersive Virtual Environments

Thomas J. Pingel, Northern Illinois University

Keith C. Clarke, University of California Santa Barbara

AutoCarto 2012 International Research Symposium

September 16-20, 2012

Columbus, Ohio


Central research question
Central Research Question: Environments

How can we, in an automatable way, produce an immersive geographic virtual environment that will assist in the interpretation, analysis, and understanding of specific, local events?


Outline
Outline Environments

  • Project overview

  • Code base

  • Terrain generation from LiDAR

  • Acquisition for of audio and video for model overlay


Immersive geographic virtual environments
Immersive Geographic EnvironmentsVirtual Environments

  • Immersive: “any virtual reality representation in which the user views her or her environment from a perspective view, and can freely move around in that environment”

  • Multiple Psychologies of Space (Montello, 1993)

    • Figural , Vista, Environmental, Geographical

  • Representing Environmental (or Geographical) spaces as Figural (or Vista) Objects while retaining some of the cognitive elements of each.

  • Emphasis on representing places in a model that can both be manipulated as an object or experienced as a place.


Related work
Related Work Environments

  • Google’s Earth and Street View

    • Microsoft & Apple

    • No ability to alter the terrain

    • Universality

  • Virtual Tübingen

    • Designed for spatial cognition testing

    • 200 structures, .5 x .15 km

    • Our study area

      • 3.25 x 1.6 km

      • ~2000 structures

Image from Virtual Tübingen


Video game community
Video Game Community Environments

  • Immense budgets and revenues

    • $65 billion annually

  • Many perspectives

    • First Person Shooters

    • World of Warcraft

    • But few environment & object perspectives

  • Highly structured environments


Code base x3d
Code Base – X3D Environments

  • XML successor to VRML (and GeoVRML)

  • Native Geo support

  • Native video texturing and spatialized audio

  • Royalty free

  • Browsers can typically read other 3D formats (e.g., COLLADA)

  • Good input device integration

    • Space M ouse

    • Microsoft Kinect

    • Wiimotes


X3d development avalon x3dom
X3D Development EnvironmentsAvalon & X3DOM

  • Integration of next-gen specs in Avalon

    • Instantreality.org

  • Integration with HTML5 with X3DOM

    • X3dom.org

  • Full rendering within browser

    • No-add ins required


Terrain generation
Terrain generation Environments

  • LiDAR

    • Cheap

    • Highly accurate

    • Portable

    • But needs processing

  • Assumption of little available geodata

    • Ground cues can be very valuable in street network ID



Terrain extraction is important
Terrain Extraction is Important Environments

Davidson Library sits approximately 6 meters above the ground due to a terrain layer error.


Terrain extraction the simple morphological filter smrf
Terrain Extraction: EnvironmentsThe Simple Morphological Filter (SMRF)

  • Emphasizes reducing Earth-as-Object error

  • Still very good at reducing Object-as-Earth error

  • Lowest total error rate of any published algorithm tested against ISPRS dataset

  • tpingel.org/code


Lidar visualization bonemaps
LiDAR Environments Visualization (Bonemaps)

  • Image-like visualization of Digital Surface Model

  • No registration errors

  • Slope-based intensity mapping, w/ compensation for “cognitive slope”

  • Higher contrast than hillshade

  • Appropriate for mixed environments


Smrf bonemaps at el pilar guatemala
SMRF + EnvironmentsBonemaps at El Pilar, Guatemala

Digital Surface Model


Smrf bonemaps at el pilar guatemala1
SMRF + EnvironmentsBonemaps at El Pilar, Guatemala

SMRF-derived terrain layer


Video overlay
Video Overlay Environments

  • Aerostat-based video capture

  • Smartphone capture and relay

  • Native video texturing in X3D


Acknowledgements
Acknowledgements Environments

  • IC Postdoc for funding the project.

  • Alan Glennon and Kitty Courier for kite photography expertise.

  • William McBride for SRMF algorithm development and aerostat design.


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