georgia tech gvu center mobile visualization in a dynamic, augmented battlespace mobile...

Georgia Tech GVU CenterGeorgia Tech GVU Center

Mobile Visualization in a Dynamic, Mobile Visualization in a Dynamic, Augmented BattlespaceAugmented Battlespace

William Ribarsky and Nickolas FaustGVU Center

Georgia Institute of Technology


VGIS, a General Framework forVGIS, a General Framework for

Global Geospatial Global Geospatial DataData and and VisualizationVisualization

• It accepts and integrates all types of geospatial data into a global framework.

• It is scalable to very large data stores and to distributed environments.

• It provides an interactive (“real time”) visualization framework.

• It supports discovery of new information via navigation in context with unfolding detail.

• It supports heterogeneous detail management.

Background:


General Data FrameworkGeneral Data Framework

•Universal Data Structure•One global hierarchy with multiple instances•A common structure for fast paging & caching•Common, image-based metrics for display•Multiple levels of detail•Evaluates Intent & Perception of user

Background:


Global Data Model: Forest of QuadtreesGlobal Data Model: Forest of Quadtrees

•32 zones•8 levels per quadtree

Background:


Global Data Model: Forest of QuadtreesGlobal Data Model: Forest of Quadtrees

•32 zones•8 levels per quadtree•Separate coodinate system at each leaf node (256x256 total nested systems)•1 mm worst case resolution

Background:


General Zonal QuadtreeGeneral Zonal Quadtree

}treestructure

Data-dependent, detailed, low-level representation

Background:


}Terrain Zonal QuadtreeTerrain Zonal Quadtree

22 levels

Regular Triangularization (1024 x 1024 grid points)

Example:


Static Object Zonal QuadtreeStatic Object Zonal Quadtree

• Buildings or other static objects– Static in organization– Uses hierarchy to around 100

meters,when closer:• Uses bounding box

detection• Uses imposters for detail

management• Uses collision detection

Example:


Time-dependent Volume Data QuadtreeTime-dependent Volume Data Quadtree

•Stacked, time-sequenced volumes for fast visualization

Example:

Geospatial Quadtree

GeolayeredVolume

Latitude

Altitu

de

Lo

ng

itud

e

Longitude cone wedge

Latitude plane wedge

ime

t


View-Dependent Detail ManagementView-Dependent Detail Management

•This example is for buildings, but the procedure has been generalized to other types of data.

Bounding dimension

Eye

Example:


World

Atlanta, GA area

Grand CanyonRwanda

Continuous Navigation Around the U.S.Continuous Navigation Around the U.S.(or World)(or World)

Results:


Atlanta

NTC

San Francisco

Savannah

Hierarchical Urban Construction: Hierarchical Urban Construction: Cities EverywhereCities Everywhere

Results:


Goals and DirectionsGoals and Directions

•Mobile and stationary visualization within a common framework•Dynamic, universal data structures with fast updates•Real-time, scalable visualization of all visual products•Multimodal interaction in multiple environments


Technical ChallengesTechnical Challenges

•Developing & evaluating an appropriate mobile visualization paradigm•Hierarchical, scalable data structures with fast access that include time, uncertainty, and varied data products•Methods for fast update of dynamic data structures•Automated detail management schemes for uncertainty and other visual products•Developing & evaluating multiple modes of interaction & navigation; matching them to different environments•Intelligent retrieval and visualization of data products


Hierarchical, Scalable Data structuresHierarchical, Scalable Data structures

treestructure

ime

t

Uncertainty,

Annotations, &

Semantics

Various low-level, detailed representations


Dynamic Data Structures & Real-time DataDynamic Data Structures & Real-time Data

Insertion of geo-registered remote sensor data

Skeleton quadtree

Properties

Dynamic Data Cache Specific Data Manager

Skip

Main MemoryPrioritized


Dynamic Data Structures & Real-time DataDynamic Data Structures & Real-time Data

Insertion of geo-registered remote sensor data

Dynamic Data Cache Specific Data Manager

Main Memory

Distributed Hard Disk

Specific Data Server

Prioritized


Multimodal Interaction in Multiple EnvironmentsMultimodal Interaction in Multiple Environments

Environments•Desktop•Laptop•Mobile (palm, HMD, larger handheld or wearable)•Virtual Workbench•Liveboard•NAVE•Others

Interaction Modes•Mouse•Joystick or Spaceball•Pen-based or touch screen•Wired 3D or wireless 3D•Head tracking, hand-tracking, gesture recognition•Voice•Others

•What are the environmental affordances?•What are user needs?•Is 3D interaction necessary?•How best to navigate large virtual spaces (2D or 3D)?•How to most effectively combine modes?•How to evaluate?


Detail Management for UncertaintyDetail Management for Uncertaintyand Other Visual Productsand Other Visual Products

Hierarchical fast clustering for 4D patterns

Interactive switching on/off and focused, adaptive views

Radar Iconzoom

zoomzoom

final leaf cluster

Viewpoint


A Battlespace Visualization TestbedA Battlespace Visualization Testbed

•Mobile and stationary visualization within a common framework

-for evaluation of concepts and tools-for integration and testing-for demonstrations


Agile, Mobile, Collaborative TestbedAgile, Mobile, Collaborative Testbed

A networked, collaborative whole Earth terrain database linking workstations, large projected displays, and mobile handheld systems. Mobile users carry systems with handheld or augmented displays providing 3D terrain visualizations. Mobile users receive, record, and transmit information about the world. Users of stationary 3D displays collect and evaluate information provided by mobile users and route data and intelligence back to mobile users. Collaboration is through annotation of thevirtual geospatial database.


Central Terrain Database

NAVE Virtual Workbench

Mobile Displays

Collaboration Channels

Wireless Terrain Datalink

Terrain Datalink

Position, Terrain Markup, Route Finding, Weather,

Friendly/Foe advisories, etc.

w/GPS, bearing, tilt sensors and wireless data.

Local databases download and cache data according to bandwidth, movement, and

rendering speed of each platform.

Wireless

Wireless

Architecture: Agile, Mobile, Collaborative TestbedArchitecture: Agile, Mobile, Collaborative Testbed


Devices: Agile, Mobile, Collaborative TestbedDevices: Agile, Mobile, Collaborative Testbed

Two mobile, wearable computers with different displays and different interfaces. The one on the left captures gestures with a camera while the one in the center uses a handheld "twiddler". On the right is the Virtual Workbench set up with a perceptual interface that captures 3D object shapes as well as hand and arm gestures.

Multiscreen, immersive, and inexpensive NAVE environment for command post operations.


Mobile, Wireless CoverageMobile, Wireless Coverage

Antenna

Georgia Tech campus testbed

georgia tech gvu center mobile visualization in a dynamic, augmented battlespace mobile...

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