geometry images

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Geometry Images Geometry Images Steven Gortler Steven Gortler Harvard University Harvard University Xianfeng Gu Xianfeng Gu Harvard University Harvard University Hugues Hoppe Hugues Hoppe Microsoft Research Microsoft Research

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Geometry Images. Xianfeng Gu Harvard University. Steven Gortler Harvard University. Hugues Hoppe Microsoft Research. Irregular meshes. Vertex 1 x 1 y 1 z 1 Vertex 2 x 2 y 2 z 2 …. Face 2 1 3 Face 4 2 3 …. Texture mapping. Vertex 1 x 1 y 1 z 1 Vertex 2 x 2 y 2 z 2 …. - PowerPoint PPT Presentation

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Page 1: Geometry Images

Geometry ImagesGeometry Images

Steven GortlerSteven GortlerHarvard UniversityHarvard University

Xianfeng GuXianfeng GuHarvard UniversityHarvard University

Hugues HoppeHugues HoppeMicrosoft ResearchMicrosoft Research

Page 2: Geometry Images

Irregular meshesIrregular meshes

Vertex 1 xVertex 1 x11 y y11 z z11

Vertex 2 xVertex 2 x22 y y22 z z22

……

Face 2 Face 2 11 3 3Face 4 2 3Face 4 2 3……

Page 3: Geometry Images

Texture mappingTexture mapping

Vertex 1 xVertex 1 x11 y y11 z z11

Vertex 2 xVertex 2 x22 y y22 z z22

……

ss11 t t11

ss22 t t22

normal mapnormal mapss

tt

Face 2 Face 2 11 3 3Face 4 2 3Face 4 2 3……

Page 4: Geometry Images

Complicated rendering processComplicated rendering process

Vertex 1 xVertex 1 x11 y y11 z z11

Vertex 2 xVertex 2 x22 y y22 z z22

……

random access!random access!

random access!random access!

ss11 t t11

ss22 t t22

Face 2 Face 2 11 3 3Face 4 2 3Face 4 2 3……

~40M ~40M ΔΔ/sec/sec

Page 5: Geometry Images

Semi-regular representationsSemi-regular representations

irregular vertex indicesirregular vertex indices only only semisemi-regular-regular

[Eck et al 1995][Eck et al 1995][Lee et al 1998][Lee et al 1998][Khodakovsky 2000][Khodakovsky 2000][Guskov et al 2000][Guskov et al 2000]……

Page 6: Geometry Images

Geometry ImageGeometry Image

geometry imagegeometry image257 x 257; 12 bits/channel257 x 257; 12 bits/channel

3D geometry3D geometrycompletely regular samplingcompletely regular sampling

Page 7: Geometry Images

Basic ideaBasic idea

demodemo

cutcut

parametrizeparametrize

Page 8: Geometry Images

Basic ideaBasic idea

cutcut

samplesample

Page 9: Geometry Images

Basic ideaBasic idea

cutcut

[[rr,,gg,,bb] = [] = [xx,,yy,,zz]]

renderrender

storestore

Page 10: Geometry Images

How to cut ?How to cut ?

sphere in 3Dsphere in 3D2D surface disk2D surface disk

Page 11: Geometry Images

How to cut ?How to cut ?

Genus-0 surface Genus-0 surface any tree of edges any tree of edges

sphere in 3Dsphere in 3D2D surface disk2D surface disk

Page 12: Geometry Images

How to cut ?How to cut ?

Genus-Genus-gg surface surface 2g 2g generator loops generator loops minimumminimum

torus (genus 1)torus (genus 1)

Page 13: Geometry Images

Surface cutting algorithmSurface cutting algorithm

(1) Find topologically-sufficient cut:(1) Find topologically-sufficient cut:22gg loops loops [Dey and Schipper 1995][Dey and Schipper 1995] [Erickson and Har-Peled 2002] [Erickson and Har-Peled 2002]

(2) Allow better parametrization:(2) Allow better parametrization:additional cut pathsadditional cut paths [Sheffer 2002][Sheffer 2002]

Page 14: Geometry Images

Step 1: Find topologically-sufficient cutStep 1: Find topologically-sufficient cut

(a) retract 2-simplices(a) retract 2-simplices

(b) retract 1-simplices(b) retract 1-simplices

Page 15: Geometry Images

Results of Step 1Results of Step 1

genus 6genus 6 genus 0genus 0genus 3genus 3

Page 16: Geometry Images

Step 2: Augment cutStep 2: Augment cut

Make the cut pass through “extrema”Make the cut pass through “extrema” (note: not local phenomena). (note: not local phenomena).

Approach: parametrize and look for “bad” areas.Approach: parametrize and look for “bad” areas.

Page 17: Geometry Images

Step 2: Augment cutStep 2: Augment cut

……iterate while parametrization improvesiterate while parametrization improves

Page 18: Geometry Images

Results of Steps 1 & 2Results of Steps 1 & 2

genus 1genus 1 genus 0genus 0

Page 19: Geometry Images

Parametrize boundaryParametrize boundary

Constraints:Constraints: cut-pathcut-path mates identical length mates identical length endpointsendpoints at grid points at grid points

aaa’a’

aa

a’a’

no cracksno cracks

Page 20: Geometry Images

Parametrize interiorParametrize interior

– optimizes point-sampled approx. optimizes point-sampled approx. [Sander et al 2002][Sander et al 2002]

Geometric-stretch metricGeometric-stretch metric– minimizes undersampling minimizes undersampling [Sander et al 2001][Sander et al 2001]

Page 21: Geometry Images

Previous metricsPrevious metrics (Floater, harmonic, uniform, …)(Floater, harmonic, uniform, …)

Stretch parametrizationStretch parametrization

Page 22: Geometry Images

SampleSample

geometry image

Page 23: Geometry Images

RenderingRendering

(65x65 geometry image)(65x65 geometry image)

Page 24: Geometry Images

renderingrendering

geometry image geometry image 2572572 2 x 12b/chx 12b/ch

normal-map image normal-map image 5125122 2 x 8b/chx 8b/ch

Rendering with attributesRendering with attributes

Page 25: Geometry Images

Advantages for hardware renderingAdvantages for hardware rendering

Regular sampling Regular sampling no vertex indices. no vertex indices. Unified parametrization Unified parametrization no texture coordinates. no texture coordinates.

Raster-scanRaster-scan traversal of traversal of sourcesource data: data: geometry & attribute samples in lockstep. geometry & attribute samples in lockstep.

SummarySummary: compact, regular, no indirection: compact, regular, no indirection

Page 26: Geometry Images

normal mapnormal map512x512; 8b/ch512x512; 8b/ch

Normal-Mapped DemoNormal-Mapped Demo

geometry imagegeometry image129x129; 12b/ch129x129; 12b/ch

demodemo

Page 27: Geometry Images

demodemocolor mapcolor map

512x512; 8b/ch512x512; 8b/ch

Pre-shaded DemoPre-shaded Demo

geometry imagegeometry image129x129; 12b/ch129x129; 12b/ch

Page 28: Geometry Images

ResultsResults

257x257257x257

normal-map 512x512normal-map 512x512

Page 29: Geometry Images

ResultsResults

257x257257x257

color image 512x512color image 512x512

Page 30: Geometry Images

Mip-mappingMip-mapping

257x257257x257 129x129129x129 65x6565x65

boundary constraintsboundary constraintsset for size 65x65set for size 65x65

Page 31: Geometry Images

Hierarchical cullingHierarchical culling

view-frustum cullingview-frustum culling

backface cullingbackface culling

geometry imagegeometry image

normal-map imagenormal-map image

Page 32: Geometry Images

CompressionCompression

1.5 KB1.5 KB

+ topological sideband (12 B)+ topological sideband (12 B)fused cutfused cut295 KB295 KB

Image wavelet-coderImage wavelet-coder

Page 33: Geometry Images

Compression resultsCompression results

1.5 KB1.5 KB 3 KB3 KB 12 KB12 KB 49 KB49 KB

295 KB 295 KB

Page 34: Geometry Images

4045505560657075808590

100 1000 10000 100000File Size (bytes)

PS

NR

(dB

)

Khodakovsky

geometry image

Rate distortionRate distortion

Page 35: Geometry Images

Some artifactsSome artifacts

aliasingaliasing anisotropic samplinganisotropic sampling

Page 36: Geometry Images

SummarySummary

Simple rendering:Simple rendering: compact, no indirection, raster-scan stream. compact, no indirection, raster-scan stream.

Mipmapped geometryMipmapped geometry Hierarchical cullingHierarchical culling CompressibleCompressible

Page 37: Geometry Images

Future workFuture work

Better cutting algorithmsBetter cutting algorithms

Feature-sensitive remeshingFeature-sensitive remeshing

Tangent-frame compressionTangent-frame compression

Bilinear and bicubic renderingBilinear and bicubic rendering

Build hardwareBuild hardware

Page 38: Geometry Images