non-invasive interactive visualization of architectural environments

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Non-Invasive Interactive Visualization of Architectural Environments. Christopher NiederauerU.C. Santa Barbara Mike HoustonStanford University Maneesh AgrawalaMicrosoft Research Greg HumphreysUniversity of Virginia. Motivation. Trackball style manipulator. Walkthrough. - PowerPoint PPT Presentation

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Non-Invasive Interactive Visualization of Architectural

Environments

Christopher Niederauer U.C. Santa BarbaraMike Houston Stanford UniversityManeesh Agrawala Microsoft ResearchGreg Humphreys University of Virginia

Motivation

Trackball style manipulator Walkthrough

Can’t see overall interior/exterior structure!

ArcBall [Shoemake 1992] [Teller 1992]

Motivation

The Idea

• Exploded view

• Non-Invasive [Mohr 2001]

Overall structure is visible!

How It’s Done

• Example Architecture: Soda Hall– Geometric Analysis (Pre-Process)

– Rendering

Geometric Analysis Rendering

GatherData

FindSplitsOpenGL

Stream

…Floor

FloorComposite

Gather Architectural Data• Intercept the OpenGL stream

– Find downward facing polygons• Requires up-vector

Geometric Analysis Rendering

FindSplits

OpenGLStream

…Floor

FloorComposite

up

GatherData

446

Gather Architectural Data• Create Histogram

286126

Height Ceiling Area

Geometric Analysis Rendering

OpenGLStream

…Floor

FloorComposite

Soda Hall Side Profile

606766942

FindSplits

GatherData

FindSplits

Find Splitting Heights

Geometric Analysis Rendering

GatherData

OpenGLStream

…Floor

FloorComposite

Offset Ceiling Heights

Offset Ceiling Heights

Rendering• Multiple Playback

(Once per Floor)

– Clipping Planes – Viewpoint Control

Geometric Analysis Rendering

GatherData

FindSplits

OpenGLStream

…Floor

FloorComposite

Cluster Speedup

Composite

Floor 1 Floor 2 Floor 3

Complete Model

Soda Hall

TrackballWalkthrough

Results with Soda Hall

(Single Floor)

Quake III: Arena

TrackballWalkthrough

Results with Quake III: Arena

(Single Floor)

Item

Video

Transparent Back-Faces

Future Directions

• Make fully automated:– Semantic inputs

• Up vector• Number of stories to split into

Future Directions

[Salomon et al, 2003]

Future Directions

(Hand Designed Mock-up)

Summary and Conclusions

• Can improve viewer comprehension

Acknowledgements

• Pat Hanrahan• John Carmack• Christopher August• DOE VIEWS Grant #B504665

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