Object space ewa surface splatting a hardware accelerated approach to high quality point rendering
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CMU Object Space EWA Surface Splatting: A Hardware Accelerated Approach to High Quality Point Rendering Liu Ren Hanspeter Pfister Matthias Zwicker Motivation Point-based graphics needs high quality texture filtering High quality point rendering lacks hardware support

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Object Space EWA Surface Splatting: A Hardware Accelerated Approach to High Quality Point Rendering

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CMU

Object Space EWA Surface Splatting: A Hardware Accelerated Approach to High Quality Point Rendering

Liu Ren

Hanspeter Pfister

Matthias Zwicker


Motivation

  • Point-based graphics needs high quality texture filtering

  • High quality point rendering lacks hardware support

  • GPU performance outpaces CPU

[Wolfman Geforce 4 demo]

Pure Hardware Accelerated + High Quality?

Yes!


Related Work

Object Space EWA Splatting EG 02


Surface Element (Surfel)

normal

y

surfel tangent plane

z

x

  • No connectivity

  • No texture maps, no normal maps, etc

2D reconstruction filter

Point-based Surface Representation


warp

screen space

object space

surfel reconstruction filter

y

x

aliasing

warped reconstruction filter

y

z

x

Surfel Rendering: Splatting


warp

screen space

object space

warped reconstructionfilter

screen space resampling filter

low-pass filter

Surfel Rendering: Screen Space EWA Filtering

reconstruction filter

  • Elliptical Weighted Average (EWA) filtering

  • EWA Splat = low-pass filter warped reconstruction filter

  • Screen space EWA splatting not supported by graphics hardware.


warp

screen space

object space

warped

low-pass filter

reconstruction

filter

tangent spaceresampling filter

low-pass filter

Surfel Rendering: Object Space EWA Filtering

  • Tangent space resampling filter = warped low-pass filter reconstruction filter

  • View dependent filter


normal

surfel tangent plane

Textured polygons

Tangent space resampling filters

Texture mapping

EWA splats in frame buffer

Additive alpha

blending

Warped surface

texture reconstruction

Hardware Accelerated Point-based Rendering


Correct visibility in hardware

?

  • No holes, hidden surface splats removal

  • Lack of A-buffer support

?

EWA resampling filter

  • View dependent

  • Texture or polygon not fixed

Challenges


1. Visibility splatting

  • Disable frame buffer updates

  • Render opaque quad for each surfel

  • Generate depth image with a small offset

2. Resampling filter splatting

  • Disable Z-buffer updates

  • Render textured polygons with additive alpha blending

Two Pass Algorithm Overview


surface

surface

occlusion artifacts

depth image

depth image

QSplat

z

z

camera space

camera space

Object Space EWA

First Pass: Visibility Splatting Schemes


elliptical gaussian (tangent space resampling filter)

texture (unit gaussian)

(0,1)

(1,1)

match

(0,0)

(1,0)

texturemapping

surfel polygon with unknown geometry

tangent space quad with known geometry

vertex computation

textured quad

Second Pass: Handle View Dependent EWA Resampling filter


Per-pixel normalization:

  • Read back data from frame buffer

  • Post-processing scheme

  • Bad for hardware acceleration

    Per-surfel normalization:

  • Pre-compute the surfel normalization weight

  • Pre-processing scheme

  • Good for hardware acceleration

without normalization

with normalization

no artifacts

varying brightness

Normalization Issues


Splatting No Filtering

V.S.

Object Space EWA Filtering

Object Space EWA / Points

V.S.

Anisotropic Texture Filtering + Accuview /Triangle Mesh

Demo: Checkerboard on Geforce 4 Ti 4600

:


Salamander

103K Surfels

Demo: Surfel Models on ATI Radeon 9700


Demo: Surfel Models on ATI Radeon 9700

Chameleon

102K Surfels


Demo: Surfel Models on ATI Radeon 9700

Wasp

273K Surfels


Demo: Surfel Models on ATI Radeon 9700

Fiesta

352K Surfels


Performance with Phong Shading


Conclusion

  • New object space formulation of EWA surface splatting

  • Completely hardware accelerated approach with negligible CPU involvement

  • Benefits from GPU performance improvements


Future Work

  • Semitransparent point models

  • View dependent BRDF shading

  • Animated point models

  • Optimization with upcoming hardware features


CMU

Acknowledgments

Jessica Hodgins, Paul Heckbert

Micheal Doggett, Evan Hart, Jeff Royle

Henry Moreton

Jennifer Pfister, Wei Li, Wei Chen

Http://www.cs.cmu.edu/~liuren/research.htm


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