feature sensitive bas relief generation
DESCRIPTION
Feature Sensitive Bas Relief Generation. Jens Kerber 1 , Art Tevs 1 , Alexander Belyaev 2 , Rhaleb Zayer 3 , and Hans-Peter Seidel 1 1 Max-Planck- Instut f ü r Informatik, Saarbr ü cken 2 Joint Research Institute for Image and Signal Processing, Edinburgh - PowerPoint PPT PresentationTRANSCRIPT
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Feature Sensitive Bas Relief Generation
Jens Kerber 1, Art Tevs 1, Alexander Belyaev 2,Rhaleb Zayer 3, and Hans-Peter Seidel 1
1 Max-Planck-Instut für Informatik, Saarbrücken2 Joint Research Institute for Image and Signal Processing, Edinburgh
3 LORIA-INRIA Loraine, CNRS, Nancy
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Motivation Aim
– Compress depth-interval size of height field– No loss of important features
Applications for Bas-Reliefs– Coinage– Packaging– Shape Decoration
Embossment Engraving Carving
– Displacement Maps
SMI 2009, Tsinghua University, Beijing, China1 http://www.cachecoins.org/2 Real-time relief mapping on arbitrary polygonal surfaces Policarpo F., Oliveira M., Comba J. L. D., SIGGRAPH 2005
1
2
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SMI 2009, Tsinghua University, Beijing, China
Naïve Approach Linear Rescaling
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Related Work Automatic generation of bas-reliefs from 3D shapes
W. Song, A. Belyaev, H.-P. Seidel, SMI 2007 (short paper)+ Introducing the problem and attempting to solve it
Digital Bas-Relief from 3D ScenesT. Weyrich, J. Deng, C. Barnes, S. Rusinkiewicz, A. Finkelstein, SIGGRAPH 2007
+ Impressive results - Much user interaction required, computationally expensive
Feature Preserving Depth Compression of Range ImagesJ. Kerber, A. Belyaev, H.-P. Seidel, SCCG 2007
+ Simple and fast - Spherical parts not well reproduced, problems with noise
Bas-Relief Generation Using Adaptive Histogram EqualizationX. Sun, P. Rosin, R. Martin, TVCG 2009
+ Very good results - Time consuming
SMI 2009, Tsinghua University, Beijing, China
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Pipeline
Gradient Extraction
Silhouette Removal
OutlierDetection
Attenuation
Decomposition
Re-assemblin
gRescaling Re-
weighting
SMI 2009, Tsinghua University, Beijing, China
I
R
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SMI 2009, Tsinghua University, Beijing, China
Silhouette Treatment Gradient of the Background mask = 1 ?
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Outlier Detection Tollerance parameter
– Deviation to mean gradient value
SMI 2009, Tsinghua University, Beijing, China
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Signal Decomposition
Base-layer and Detail-layer Detail Enhancement Base Compression
SMI 2009, Tsinghua University, Beijing, China
DetailBase1
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Gradient domain Edge preservation
Gradient extrema preservation
Spatial Domain Preservation of ridges
and valleys
Curvature extrema preservation
SMI 2009, Tsinghua University, Beijing, China
Bilateral Filter
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Reweighting
SMI 2009, Tsinghua University, Beijing, China
Before After
X-Gradient
Y-Gradient
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SMI 2009, Tsinghua University, Beijing, China
Poisson Reconstruction Given Ix, Iy
Compute Ixx + Iyy = ΔI
Partial Differential Equation
Well studied Problem
Multi-Grid-Solver– Assumption: Frame equals background
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Results
SMI 2009, Tsinghua University, Beijing, China
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Cubism Ancient technique in art Combine multiple viewpoints in a single painting
Aim: extend this effect from 2D to sculpting
SMI 2009, Tsinghua University, Beijing, China 3 http://picasso.tamu.edu/picasso/
3 3
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Height Field Capturing
Open GL Application 180˚ in 15˚ steps Composition in 2D
SMI 2009, Tsinghua University, Beijing, China
0
-30
30 75
-75
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Transition Problems Transition areas
– Seams are automatically detected as outliers– But set to 0– Flat transitions would emphazise the impression
of having two different parts
SMI 2009, Tsinghua University, Beijing, China
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Transition Problems (ctd.) 0-Gradient affects 3x3 neighborhood Re-fill affected area Weighted average (Gauss) excluding masked entries
Seamless results
SMI 2009, Tsinghua University, Beijing, China
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Results
SMI 2009, Tsinghua University, Beijing, China
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Performance
SMI 2009, Tsinghua University, Beijing, China
Intel 4x2.6 GHz, 8GB, Matlab64 Implementation Bottleneck
– Bilateral Filter– Poisson Reconstruction
Not optimized yet, possible acceleration
Model Resolution / pixel Time / secondsLucy 950x800 6.2
Lion-Vase 950x800 6.8
XYZRGB Dragon 980x1700 13.5
David Cubism 1 1200x1200 17.2
David Cubism 2 800x800 8.1
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Conclusion
Contribution– Little user intervention– Preservation of fine and sharp structural details– More artistic freedom– Potentially Fast– Independent of complexity– Commercial applications
SMI 2009, Tsinghua University, Beijing, China
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SMI 2009, Tsinghua University, Beijing, China
Future work Dynamic extension
– Video
Thank you for your attention!