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Title: Matthias Trapp, Tassilo Glander, Henrik Buchholz, Jrgen Dllner


1
3D Generalization Lensesfor Interactive Focus
Context Visualizationof Virtual City Models
  • Matthias Trapp, Tassilo Glander, Henrik Buchholz,
    Jürgen Döllner
  • Hasso-Plattner-Institut,
  • University of Potsdam Germany
  • 12th International ConferenceInformation
    Visualization9-11 July 2008

2
Motivation Virtual 3D City Models
  • Properties
  • Large number of objects
  • High degree of visual detail
  • Tool for communicate complex 3D geoinformation
  • Numerous applications
  • ? Can lead to perceptional and cognitive overload

3
Motivation Generalized Virtual 3D City Models
Glander, ACMGIS 2007, ICA WS 2008
4
Motivation Combined Generalization Levels
  • Simple case
  • Single arbitrarily shaped, non-convex volume
    (lens shape)
  • Two Levels of Abstraction (LOA)
  • Model Complexity lt 500 MB (Geometry Textures)

Context (LOA1)
3D Lens Shape
5
Motivation Combined Generalization Levels
  • Complex case
  • 3 intersecting lens shapes (multiple foci)
  • Three Levels of Abstraction
  • Model Complexity gt 2GB
  • Challenges
  • Interactive manipulation of lens shapes
  • Combined usage (intersection, nesting) of
    multiple lenses
  • Enabling arbitrary lens shapes
  • Handling spatial data complexity

6
Outline
  • Related Work
  • Conceptual Overview
  • Preprocessing Focus Context Mappings
  • Real-Time Rendering
  • Application Examples
  • Future Work Conclusions

7
Related Work
  • Interactive 3D Focus Context Visualization with
    Lenses
  • 3D Magic LensesViega et. al, UIST 1996
  • A Solution for the Focus and Context Problem in
    Geo-Virtual EnvironmentsRopinski et. al, DMGIS
    2005
  • Real-Time Volumetric Tests Using Layered Depth
    ImagesTrapp and Döllner, Eurographics 2008
  • Generalization
  • 2D Building Simplification Aggregatione.g.,
    Mayer, ISPRS 1998
  • Single 3D Building Simplificatione.g., Kada,
    ISPRS WS 2006
  • 3D Cell-Based City Model GeneralizationGlander
    and Döllner, ACMGIS 2007

8
Our Approach Conceptual Overview
  • Preprocessing Phase
  • Create levels of abstraction (LOA) and
    volumetric depth sprites (VDS)
  • Rendering Phase
  • Create / modify focus context mapping FNC
    map(VDS, LOA)
  • Real-time image synthesis render(FNC)

9
Automatic Generalization of Virtual 3D City Models
  • Input City Model CM
  • Output Levels of Abstraction LOA
  • Process

10
Preprocessing of Lens Volumes
  • Input Derived or modeled solid polygonal shapes
    S
  • Output Volumetric Depth Sprites VDS
  • Processing

11
Mapping Generalization Levels to Lens Volumes
  • Mapping for n lenses and generalization levels
  • Mapping Properties
  • Prioritized, hierarchical one-to-one mapping (i
    priority)
  • Additional attributes (colors, lens positioning
    scaling,)
  • Mapping can be changed at run-time

12
Real-time Rendering of Focus Context Mapping
  • Multi-pass rendering clipping against VDS
  • First pass render context
  • Successively one pass per LOA
  • Start with lowest priority i n

13
Applications Examples Usage Scenarios
  • Scene Lens with intersecting foci of multiple
    non-convex volumes

14
Applications Examples Usage Scenarios
  • Camera Lens with nested foci of the same convex
    volume

15
Limitations Future Work
  • Current conceptual limitations
  • Only one-to-one mapping possible
  • Model complexity requires out-of-core rendering
  • Clipping limitations
  • Under-sampling / aliasing artifacts
  • No capping of clipped areas
  • Future Work
  • Extend mapping mechanism one-to-many
  • Compensate sampling artifacts
  • Enable capping of clipped areas
  • Use cases that exploit technical potential

16
Conclusions
  • Wrap-up
  • Concept technique for combing different levels
    of generalization
  • Two phase process preprocessing rendering
  • Hierarchical focus content mapping
  • Interactive multi-pass rendering
  • Potential for future work

17
Thank You
  • Contact
  • Matthias Trapp matthias.trapp_at_hpi.uni-potsdam.de
  • Tassilo Glander
  • tassilo.glander_at_hpi.uni-potsdam.de
  • Henrik Buchholz
  • henrik.buchholz_at_hpi.uni-potsdam.de
  • Computer Graphics Systems Group Prof. Dr.
    Jürgen Döllner www.hpi.uni-potsdam.de/3d
  • Researchgroup 3D-Geoinformation www.3dgi.de

18
Main References
  • Glander, Döllner, Cell-Based Generalization of 3D
    Building Groups with Outlier Management, ACMGIS,
    2007
  • Kada 3D Building Generalization Based on
    Half-Space Modeling, Proceedings of the ISPRS
    Workshop on Multiple Representation and
    Interoperability of Spatial Data, 2006
  • Mayer Model-Generalization of Building Outlines
    on Scale-Spaces and Scale-Space Events,
    International Archives of Photogrammetry and
    Remote Sensing, Vol. 33, 1998
  • Trapp, Döllner, Real-Time Volumetric Tests Using
    Layered Depth Images, Eurographics 2008
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