Modeling Anisotropic Surface Reflectance with Example-Based Microfacet Synthesis Jiaping Wang1, Shuang Zhao2, Xin Tong1 John Snyder3, Baining Guo1 Microsoft Research Asia1 Shanghai Jiao Tong University2 Microsoft.
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Modeling Anisotropic Surface Reflectance with Example-Based Microfacet Synthesis
Jiaping Wang 1 , Shuang Zhao 2 , Xin Tong 1 John Snyder 3 , Baining Guo 1
Microsoft Research Asia
1
Shanghai Jiao Tong University
2
Microsoft Research
3
Surface Reflectance
satin metal wood
Anisotropic Surface Reflectance
isotropic anisotropic
Our Goal
modeling spatially-varying anisotropic reflectan
ce
Surface Reflectance in CG
• 4D BRDF
ρ
(
o
,
i
) – B idirectional R eflectance D istribution F unction – how much light reflected wrt in/out directions
o i
Surface Reflectance in CG
• 4D BRDF
ρ
(
o
,
i
) – B idirectional R eflectance D istribution F unction – how much light reflected wrt in/out directions • 6D Spatially-Varying BRDF: SVBRDF
ρ
(
x
,
o
,
i
) – BRDF at each surface point
x
Related Work I
• parametric BRDF models – compact representation – easy acquisition and fitting – lack realistic details parametric model [Ward 92] ground truth
Related Work II
• tabulated SVBRDF – realistic – large data set – difficult to capture • lengthy process • expensive hardware • image registration light dome [Gu et al 06]
Related Work II
• tabulated SVBRDF – realistic – large data set – difficult to capture • lengthy process • expensive hardware • image registration light dome [Gu et al 06]
Microfacet BRDF Model
• surface modeled by tiny mirror facets [Cook & Torrance 82]
Microfacet BRDF Model
• surface modeled by tiny mirror facets [Cook & Torrance 82] normal distribution shadow term fresnel term
Microfacet BRDF Model
• based on Normal Distribution Function (NDF) – NDF
D
is 2D function of the half-way vector
h
– dominates surface appearance
Challenge: Partial Domains
• samples from a single viewing direction
i
– cover only a sub-region
h
Ω of NDF – How to obtain the full NDF?
partial region partial NDF complete NDF
Solution: Exploit Spatial Redundancy
• find surface points with
similar but differently rotated
NDFs material sample partial NDF at each surface point
Example-Based Microfacet Synthesis
partial NDF to complete + other surface points + rotated partial NDFs = completed NDF
Comparison ground truth isotropic Ward model our model anisotropic Ward model
Overall Pipeline
• BRDF Slice Capture • Partial NDF Recovery • Microfacet Synthesis
Overall Pipeline
• BRDF Slice Capture • Partial NDF Recovery • Microfacet Synthesis
Device Setup
• Camera-LED system, based on [Gardner et al 03] Camera
Capturing Process
Overall Pipeline
• BRDF Slice Capture • Partial NDF Recovery • Microfacet Synthesis
NDF Recovery
• invert the microfacet BRDF model Measured BRDF , Unknown Unknown NDF Shadow Term [Ashikhmin et al 00]
NDF Recovery (con’t)
• iterative approach [Ngan et al 05] – solve for NDF, then shadow term – works for complete 4D BRDF data 1.
2.
, [Ngan et al 05] [Ashikhmin et al 00]
Partial NDF Recovery
• biased result on incomplete BRDF data ground truth [Ngan et al. 05] NDF shadow term NDF shadow term
Partial NDF Recovery (con’t)
• minimize the bias – isotropically constrain shadow term in each iteration before constraint after constraint
Recovered Partial NDF
ground truth [Ngan et al. 05] our result
Overall Pipeline
• Capture BRDF slice • Partial NDF Recovery • Microfacet Synthesis
Microfacet Synthesis
partial NDF to complete Merged partial NDFs completed NDF
Microfacet Synthesis (con’t)
• straightforward implementation: For
N
NDFs at each surface point Match against
(N-1)
NDFs at other points In
M
rotation angles for alignment • number of rotations/comparisons:
N 2 *M ≈
5 × 10 11
(N ≈
640k
, M ≈
1k
)
Synthesis Acceleration
• • – complete representative NDFs only (1% of full set) For
N
NDFs in each surface point Match with
(N -1)
NDFs in other location In
M
rotation angles for alignment • times of spherical function rotation and comparison
N 2 * M ≈
5 × 10 11
N' 2 * M ≈
5 × 10 7
( N ≈ ( N' ≈
640k 6.4k
) )
Synthesis Acceleration
• • • • – complete representative NDFs only (1% of full set) For
N
NDFs in each surface point
(N -1)
NDFs in other location – In
M
rotation angles for alignment
N 2 * M ≈
5 × 10 11
N' 2 * M ≈
5 × 10 7
N'* log(N'* M) ≈
5 × 10 5
( N ≈
640k
( N' ≈
6.4k
) )
Performance Summary
• 5-10 hours for BRDF slice acquisition in HDR – 1 Hour for acquisition in LDR • 2-4 hours for image processing • 2-3 hours for partial NDF recovery • 2-4 hours for accelerated microfacet synthesis On a PC with Intel Core TM 2 Quad 2.13GHz CPU and 4GB memory
Model Validation
• full SVBRDF dataset [Lawrence et al. 06] – data from one view for modeling – data from other views for validation
Validation Result
Limitations
• • visual modeling, not physical accuracy single-bounce microfacet model – retro-reflection not handled • spatial redundancy of rotated NDFs – easy fix by rotating the sample
Rendering Result: Satin
Rendering Result: Wood
Rendering Result: Brushed Metal
Conclusions
• model surface reflectance via microfacet synthesis – general and compact representation – high resolution (spatial & angular), realistic result – easier acquisition: single-view capture cheap device shorter capturing time
Future Work
• performance optimization – capturing and data processing • extension to non-flat objects • extension to multiple light bounce
Acknowledgements
• Le Ma for electronics of the LED array • Qiang Dai for capturing device setup • Steve Lin, Dong Xu for valuable discussions • Paul Debevec for HDR imagery • Anonymous reviewers for their helpful suggestions and comments