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Physically-based Cosmetic Rendering CASA 2013

Physically-based Cosmetic Rendering CASA 2013. Cheng-Guo Huang, Tsung-Shian Huang, Wen-Chieh (Steve) Lin, and Jung-Hong Chuang Department of Computer Science National Chiao Tung University, Taiwan. Introduction. Simulating makeup effects is important in facial animation

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Physically-based Cosmetic Rendering CASA 2013

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  1. Physically-based Cosmetic RenderingCASA 2013 Cheng-Guo Huang, Tsung-Shian Huang, Wen-Chieh (Steve) Lin, and Jung-Hong Chuang Department of Computer ScienceNational Chiao Tung University, Taiwan

  2. Introduction Simulating makeup effects is important in facial animation cosmetics industry: preview, design, training http://www.fauske.com/ http://www.makeupstudio.in/blog/2013/02/ 2

  3. Existing Approaches Makeup transfer many based on image processing techniques Simple & intuitive Fixed view & lighting Shape distortion Limited effects Cosmetic simulation focus on measurement validation by simulation More computation Dynamic view & lighting Realistic Flexible effects No skin translucency 3

  4. Our Goals Physically-based cosmetic simulation Dynamic viewing and lighting Flexible effects Realistic cosmetic appearance Multilayered structure Kubelka-Munk (K-M) model with measurement of cosmetics Plausible skin rendering Translucency 4

  5. Related Work on Makeup Transfer 2D image warping [Tong et al. PG’07] [Guo and Sim CVPR’09] shape distortion, similar view 3D facial database + 2D input image [Scherbaum et al. EG’11] need makeup database fixed makeup effects 5

  6. Related Work on Cosmetic Simulation Estimate skin color with foundations by K-M model [Doi et al. 05] Simulate foundation using Cook-Torrance and PCA [Moriuchi et al. 09] Both focus on measurement No skin translucency Only consider foundations 6

  7. Approach Overview Compute reflectance & transmittance of cosmetics layers by K-M Model Skin rendering by screen space subsurface scattering Skin Combine skin radiance with cosmetics radiance

  8. Approach Overview Cosmetics Compute reflectance & transmittance of cosmetics layers by K-M Model Cosmetic Map Absorption Coefficients Scattering Coefficients Skin rendering by screen space subsurface scattering Face Combine skin radiance with cosmetics radiance 3D Mesh Normal Map Diffuse Reflectance Map

  9. One-layer Kubelka-Munk (K-M) Model • Widely used theoretical model of reflectance • Assume isotropic scattering and planar parallel layers • Simplify a radiation field into two opposite radiation fluxesI and J in +x and -x directions • Describe reflectance & transmittance by descriptive coeffs. K: absorption S: scattering

  10. Multi-layered K-M Model R1 T1R2T1 T1R2R2R1T1 Layer 1 T1R2R1 T1R2 T1 Layer 2 T1T2 T1R2R1T2

  11. S and K coefficients in K-M model • Scattering coeff. S and absorption coeff. K can be computed by • Rg, R∞, and R0 are measured spectral reflectance of background, thick and thin layer

  12. Measure reflectance Rg, R∞, and R background thick layer thin layer

  13. Sample Container • To measure R0 and R∞ • paint samples on background directly • or in shallow and deep notches (0.15 mm, 2 mm) double-sided tape Sample loaded Empty container

  14. Measurement Devices Cosmetic sample container Spectroradiometer D55 light source

  15. Measure and process data • Use spectroradiometer to capture the radiant energy at different wavelengths, • Reflectance is obtained by removing the radiant energy of light • EL is measured on 99% barium sulfate (BaSO4)

  16. Skin Subsurface Scattering • Adopt screen-space subsurface scattering [Jimemez et al. TAP’08] • Diffusion approximation: Texture  Screen space

  17. Specularity • K-M model only handles diffuse reflectance • Need to compute specularity for each layer • Use BRDF specular model to compute [Kelemen et al. 01, Dorsey and Hanrahan 96] Specular - cosmetic K-M model Specular – all layers Specular - skin

  18. Results • Measure 5 foundations, 2 blushes, 7 lipsticks • Implementation: DirectX 10, HLSL, Intel Core i5 750 2.67GHz CPU, 4GB RAM, NVIDIA GTX 260 graphics card • Rendering performance: 170 - 175 FPS • Different cosmetics can be changed in real-time, including thickness and brand

  19. 0.015 mm 0.075 mm 0.15 mm F1 F2 F3 F4 F5

  20. 2 Blushes 7 Lipsticks 0.15 mm 0.3 mm B1 B2 Orig. Skin L4 L1 L5 L2 L6 L3 L7

  21. Results: Digital Coco (a) Cosmetic map (c) F1, L1, B1 (d) F5, L1, B1 (e) F5, L3, B2 (f) F3, L3 (b) Original

  22. Results: Digital Orange F1, L7, B1 F3, L6, B1

  23. Comparison with real makeup

  24. Limitations • No pearl and sparkle effects • Not handle cosmetics in sparse powder form • Not handle translucency of cosmetics

  25. Conclusion • Simple approach to realistically render cosmetics on human skin by combining • screen-space skin rendering method • Kubelka-Munk model • Provide flexible user control on cosmetic thicknesses, brands, and patterns in real time

  26. Acknowledgements • National Science Council of Taiwan • Industrial Technology Research Institute • Next Media

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