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Shape-aware Volume
Illustration
Wei Chen,
Zhejiang University, Purdue University
Aidong Lu,
University of North Carolina at Charlotte
David S. Ebert, Purdue University
Contents
Motivation & Related Work
The Main Idea
Algorithm & Implementation
Experimental Results
Conclusions & Future Work
Motivation
Illustration is a visual representation
Motivation
Previous work on simulating appearance
 Rendering primitives: point, line, surface... drawings [LEM
02, BKR 05, FBS05]
Motivation
Previous work on simulating
appearance
 Visibility guided or selective illustration: [DWE03, CSC06,
VKG04, BG06, BGKG06, ONOI04]
Motivation
Previous work on simulating
appearance
 System work: VolumeShop [BG05], IVIS[SDS05]…
Motivation
 Most previous work relies on transfer functions
to express important features
 Expressiveness is greatly influenced by the
shape and shape variations
Related work
Volume Illustration
 Incorporate NPR techniques into volume
rendering. Ebert et al. [ER00]
 Illustrate the internal structures by synthesizing a
2D texture on the cutting planes of polygonal
models. Owada et al. [ONOI04]
 Hardware-accelerated volume illustration
[SE03,HBH03, BG05, SES05, BG06]
Related work
Volume Illustration
Related work
Shape Representation and Processing
 Boundary representation
 Volumetric Representation
Voxelization
/Distance field computation
Marching Cube
Related work
Volumetric Manipulation
 Traditional GPU-based volume deformation
techniques [RSSSG01], [WRS01]
 Feature-aligned volume deformation [CSC06]
 VolumeShop system [BG05]
Related work
Example-based Modeling and Rendering




Texture Synthesis [WM01]
Image & Curve Analogy [HJO01] [HOCS02]
Mesh Contour Analogy [ZG04]
Example-based Volume Illustration [Lu2005]
The Key Idea
Creating volume illustration in a shapeaware manner
 A shape-aware volume representation
 Curve analogy based shape deformation
 Shape-aware volume illustration
The pipeline
Volume Segmentation
Available Segmentation Approaches
 Manual segmentation
 Threshold-based or TF guided segmentation
 Level-set based segmentation (ITK)
Volume Binarization
0
The bone
2
1
The foot dataset
The skin
Volume Filtering
Volume Filtering For Binary Volume
 Image Morphology Algorithms
 Level-set based segmentation (ITK) [Whi00]
Geometric Processing
Feature Preserving Mesh Processing
 Mesh smoothing [JDD03]
 Mesh repairing [Ju04]
 Mesh simplification [ZG02]
#V 229,298
#V 13,689
Geometric Processing
Another example for the hand model
Curve Analogy Based Surface Deformation
Shape Variations are to be considered
 Using gradient domain based surface deformation
techniques [SLCo05,YZX04]
 Curve Analogy based shape deformation [ZHS05]
 Introducing a proxy surface and connecting both surfaces
with mean value coordinates [JSW05]
?
Curve Analogy Based Deformation
 For a model M0, generate a simplified model M1
 Generate the mean value coordinates for each vertex of
M0 associated with M1
 Specify a curve C1 in M1 and project it to the 2D plane
 Draw a curve C0 in the 2D illustration
 Deform C1 with respect to C0
 Deform M1 with the deformed C1 by the mesh deformation
algorithm
 Deform M0 by applying the mean-value coordinates to the
deformed M1
Simplification
M0 (#V 11067)
Deformation
M1 (#V 1917)
Deformed M1
MVC
Deformed M0
Curve Analogy Based Deformation
Apply deformation to another model
Deformation
Skin (#V 1917)
Computing Mean
Value Coordinates
Bone (#V 13689)
Deformed Skin
Applying Mean Value
Coordinates
Deformed Bone (#V 13689)
Curve Analogy Based Deformation
……
Specify a curve C1 in M1 and project it to the 2D plane
Draw a curve C0 in the 2D illustration
Deform C1 with respect to C0 using Laplacian editing [SLCo05]
Deform M1 with the deformed C1 by the mesh deformation
algorithm [ZHS05]
 ……
C1





Deformed C1
C1
C0
C1
C0
M1
Deformed M1
Shape-aware Volume Representation
A combination of a distance volume and
a segmentation volume
 Each voxel records a distance value and a
segmentation identification
The distance volume
The segmentation volume
Their composition
Shape-aware Volume Representation
Compute the signed distance volume
 Construct an auxiliary octree grid to accelerate
the computation of the distance volume [Ju04]
 Encode the distance as an unsigned integer
 Integrate all polygonal models into a single
model, and compute its distance volum.
 Compute a distance volume for each individual
object
Shape-aware Volume Representation
Generate the segmentation volume
 Based on the computed distance volumes
 Each voxel of the segmentation volume is first
initilized as zero
 For each distance volume of the ith model,
check the sign of each voxel
• If it is negative, the corresponding voxel in the
segmentation volume is assigned an identification i
6
5
4
3
2
3
4
5
The input model i
5
4
3
2
1
2
3
4
4
3
2
1
0
1
2
3
3 2 1 1 2 3 4 5
2 1 0 0 1 2 3 4
1 0 -1 -1 0 1 2 3
0 -1 -2 -2 -1 0 1 2
-1 -2 -2 -2 -2 -1 0 1
0 -1 -1 -1 -1 -1 -1 0
1 0 0 0 0 0 0 1
2 1 1 1 1 1 1 2
6
5
4
3
2
1
2
3
The distance volume
i
The segmentation volume
Offset Volume
Generate an offset volume by choosing all
points satisfying dist(p)<t
Useful to illustrate the object boundary
May build a thin offset volume form each
distance volume
Blue:
muscle
Yellow: bone
Green: bone boundary
Red:
skin
Benefits of New Representation
 Gives a novel explanation to the data and yields
a direct expression of shape
 Reconstruct smooth boundaries by exploiting the
information of the distance volume
 Be able to distinguish individual objects
Shape-aware Volume Illustration
The representation and deformation
scheme can achieve two goals.
 Suitable for applying various rendering styles to different
regions of interest.
 Mimic artistic styles for object boundaries.
 Any volume rendering system can render the
new representation
 Our implementation is based on IVIS volume illustration
system [SDS05].
 The volume is encoded in two volume textures.
Shape-aware Volume Illustration
The Uniform Illustration Equation
 Solid Texturing
 Color Shading
 Opacity Modulation
Directly interpolate the computed colors
(in RGBA space) on the eight nearest
voxel centers
 Yields better results
 Takes about eight times the computational cost
Experimental Results
P4 3.2 GHz, 1.5G RAM
nVidia Quadro FX 3400
Cg shading language
Data
#input
#Output
#Segments
Brain
78x110x64
128x128x128
8
Kidney
256x256x64
256x256x64
2
Bunny
512x512x361
256x256x256
2
Head
256x256x256
256x256x256
4
Hand
256x128x256
256x256x256
6
Experimental Results
IVIS system
3D texture slicing number: 1000
Image resolution: 480x480
Data
I
Brain
II
III
FPS
2.0 s 5.0 s
480 s
2.5
Kidney 1.2 s 2.0 s
110 s
12.0
Bunny
1.2 s 2.0 s
620 s
2.0
Head
2.0 s 3.0 s
750 s
3.0
Hand
2.0 s 5.0 s
680 s
6.0
Foot Deformation
Shape-aware Volume Rendering
Bunny Deformation
Hand Example
MRI Brain Data Example
Kidney Data Example
Conclusions
Contributions
1
The idea
Incorporating
shape into
volume
illustration
2
Algorithm
•New representation
•Curve analogy
based deformation
•Mixed volume
illumination equation
3
Applications
•Enhance the
creation capability
•Allows efficient
illustration of the
deformation
of solid space
Future Work
More efficient algorithm
 Represent and learn intrinsic artistic shape
styles from hand-drawn images
 Optimize computing of the distance volume
Deformation-driven volume
illustration of dynamic scenes
Model-based volume illustration for
special objects
Acknowledgements






Tao Ju (Washington University in St. Louis)
Kun Zhou (Microsoft Research Asia)
Xinguo Liu, Jing Huang (Zhejiang University)
Nikolai Svakhine (Adobe)
Oliver Deussen (Uni-Kanstanz university, Germany)
Stefan Bruckner (Tu Wien, Austria)
 The Hand dataset is the courtesy of Tiani Medgraph, Austria.
 NSF of China (No.60503056)
 DOE DE-FG02-06ER25733, NSF 0633150, EPA VisualGrid
 NSF Grants 0081581, 0121288, 0328984, and the U.S.
Department of Homeland Security.
[email protected]
http://web.ics.purdue.edu/~chen23
Work Pipeline of Volume Illustration
3D/4D Data Field
Raw Data
Data
Acquisition
?
Input Data
Data
Preprocess
?
Final Result
Interactive
Illumination
!
2D Illustration
?
Post-process
Work Pipeline of Volume Illustration
3D/4D Data Field
Raw Data
Data
Acquisition
Input Data
Data
Preprocess
!
Final Result
Interactive
Illumination
2D Illustration
Post-process