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:

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

  • Project overview

  • Code base

  • Terrain generation from LiDAR

  • Acquisition for of audio and video for model overlay


Immersive geographic virtual environments

Immersive Geographic Virtual 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

  • 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

  • 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

  • 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 DevelopmentAvalon & 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

  • LiDAR

    • Cheap

    • Highly accurate

    • Portable

    • But needs processing

  • Assumption of little available geodata

    • Ground cues can be very valuable in street network ID


Point cloud of building and surrounding area

Point cloud of building and surrounding area


Terrain extraction is important

Terrain Extraction is Important

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


Terrain extraction the simple morphological filter smrf

Terrain Extraction: The 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 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 + Bonemaps at El Pilar, Guatemala

Digital Surface Model


Smrf bonemaps at el pilar guatemala1

SMRF + Bonemaps at El Pilar, Guatemala

SMRF-derived terrain layer


Video overlay

Video Overlay

  • Aerostat-based video capture

  • Smartphone capture and relay

  • Native video texturing in X3D


Acknowledgements

Acknowledgements

  • 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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