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Efficient Acquisition and Realistic Rendering of Car Paint Johannes Günther, Tongbo Chen, Michael Goesele, Ingo Wald, and Hans-Peter Seidel MPI Informatik.

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Presentation on theme: "Efficient Acquisition and Realistic Rendering of Car Paint Johannes Günther, Tongbo Chen, Michael Goesele, Ingo Wald, and Hans-Peter Seidel MPI Informatik."— Presentation transcript:

1 Efficient Acquisition and Realistic Rendering of Car Paint Johannes Günther, Tongbo Chen, Michael Goesele, Ingo Wald, and Hans-Peter Seidel MPI Informatik Saarbrücken, Germany

2 November 18, 2005VMV, Erlangen, Germany2 Motivation Virtual prototyping, car design by computer Mainly two materials –Glass: ok, physical properties well known –Car paint: not so easy Goal: Realistic appearance of virtual cars, close to reality Phong BRDF: plastic look

3 November 18, 2005VMV, Erlangen, Germany3 Introduction & Previous Work Efficient Acquisition –Measurement Setup –BRDF Representation and Modelling Realistic Rendering –BRDF Evaluation –Illumination –Simulation of Sparkling Results Conclusion & Future Work Outline

4 November 18, 2005VMV, Erlangen, Germany4 Previous Work BRDF Acquisition [Marschner 98, Matusik 03] –Image based, automatic fast Car paint [Ershov 01, 04] –Complex models, many effects –Not designed for animation context Illumination by Environment Maps [Debevec 98] Realtime Ray Tracing [Wald 01, 04]

5 November 18, 2005VMV, Erlangen, Germany5 Introduction & Previous Work Efficient Acquisition Realistic Rendering Results Conclusion & Future Work Outline

6 November 18, 2005VMV, Erlangen, Germany6 Measurement Setup CCD camerawhite LED turn tablepainted sphere

7 November 18, 2005VMV, Erlangen, Germany7 Measurement Process Turn table: rotate light source 180° every 1° At each position: take HDR image –One view direction, one light direction –Sphere: each pixel different normal many BRDF sample at once Time: ca. 30 minutes per target

8 November 18, 2005VMV, Erlangen, Germany8 Targets

9 November 18, 2005VMV, Erlangen, Germany9 Modeling Use Cook-Torrance BRDF –physically derived (micro facets) –showed to perform well [Ngan EGSR 05] Non-linear fitting Multiple lobes to account for nature of car paints

10 November 18, 2005VMV, Erlangen, Germany10 reflectance φ Modeling Use Cook-Torrance BRDF –physically derived (micro facets) –showed to perform well [Ngan EGSR 05] Non-linear fitting Multiple lobes to account for nature of car paints base color highlight (clear coat) glitter (flakes)

11 November 18, 2005VMV, Erlangen, Germany11 Introduction & Previous Work Efficient Acquisition Realistic Rendering Results Conclusion & Future Work Outline

12 November 18, 2005VMV, Erlangen, Germany12 Complex Illumination HDR Environment Maps for direct illumination Options for BRDF evaluation: a)Sample Environment Map –Discretize into directional lights [Kollig 03, Agarwal 03, …] –Works well for diffuse BRDFs b)Sample BRDF –Good for specular BRDFs Decompose car paint BRDF into diffuse part and highly specular part reflectance φ split highly specular mostly diffuse car paint BRDF

13 November 18, 2005VMV, Erlangen, Germany13 Sparkles Prominent feature of metallic paints Tiny bright spots when viewed from close distance Caused by mirror-like flakes Reflect light directly to eye base color flakes clear coat

14 November 18, 2005VMV, Erlangen, Germany14 Modeling Flakes Coherent sparkles during animation Model flakes explicitly (the normal) (Integrated) sparkles appear as glitter in BRDF Derive statistical flake distribution from fitted glitter lobe Use procedural normal map Flakes are very small anti-aliasing by over sampling

15 November 18, 2005VMV, Erlangen, Germany15 Introduction & Previous Work Efficient Acquisition Realistic Rendering Results Conclusion & Future Work Outline

16 November 18, 2005VMV, Erlangen, Germany16 Model Comparison Phong ClearCoat BRDF tablefitted BRDF

17 November 18, 2005VMV, Erlangen, Germany17 Video

18 November 18, 2005VMV, Erlangen, Germany18 Conclusion Easy-to-build and fast acquisition system Measured car paint and measured lighting environment for convincing car renderings Frame-to-frame coherent sparkling simulation Future Work –Extend car paint database –Multi-level methods for sparkles (avoid aliasing)

19 November 18, 2005VMV, Erlangen, Germany19 Project homepage: Data sets available

20 November 18, 2005VMV, Erlangen, Germany20 Project homepage: Thank You Questions?

21 November 18, 2005VMV, Erlangen, Germany21

22 November 18, 2005VMV, Erlangen, Germany22 Performance vs. Quality 640 × lights no over sampling 12.1 fps 640 × lights 16 spp 1.3 fps 1280 × lights 64 spp 97 sec Cluster of 20 dual Opteron 2.5 GHz PCs Vary parameter to tune rendering speed or quality

23 November 18, 2005VMV, Erlangen, Germany23 Offline Rendering

24 November 18, 2005VMV, Erlangen, Germany24 The Different Car Paints


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