Shape-aware Volume Illustration

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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

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Contents
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Motivation

• Illustration is a visual representation

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Motivation

• Previous work on simulating appearance
• Rendering primitives point, line, surface...
  drawings LEM 02, BKR 05, FBS05

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Motivation

• Previous work on simulating appearance
• Visibility guided or selective illustration
  DWE03, CSC06, VKG04, BG06, BGKG06, ONOI04

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Motivation

• Previous work on simulating appearance
• System work VolumeShop BG05, IVISSDS05

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Motivation

• Most previous work relies on transfer functions
  to express important features
• Expressiveness is greatly influenced by the shape
  and shape variations

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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

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Related work

• Volume Illustration

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Related work

• Shape Representation and Processing
• Boundary representation
• Volumetric Representation

Voxelization /Distance field computation
Marching Cube
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Related work

• Volumetric Manipulation
• Traditional GPU-based volume deformation
  techniques RSSSG01, WRS01
• Feature-aligned volume deformation CSC06
• VolumeShop system BG05

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Related work

• Example-based Modeling and Rendering
• Texture Synthesis WM01
• Image Curve Analogy HJO01 HOCS02
• Mesh Contour Analogy ZG04
• Example-based Volume Illustration Lu2005

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The Key Idea

• Creating volume illustration in a shape-aware
  manner
• A shape-aware volume representation
• Curve analogy based shape deformation
• Shape-aware volume illustration

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The pipeline
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Volume Segmentation

• Available Segmentation Approaches
• Manual segmentation
• Threshold-based or TF guided segmentation
• Level-set based segmentation (ITK)

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Volume Binarization
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The foot dataset
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Volume Filtering

• Volume Filtering For Binary Volume
• Image Morphology Algorithms
• Level-set based segmentation (ITK) Whi00

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Geometric Processing

• Feature Preserving Mesh Processing
• Mesh smoothing JDD03
• Mesh repairing Ju04
• Mesh simplification ZG02

V 229,298
V 13,689
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Geometric Processing

• Another example for the hand model

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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

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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
MVC
Deformation
M1 (V 1917)
Deformed M1
Deformed M0
M0 (V 11067)
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Curve Analogy Based Deformation

• Apply deformation to another model

Deformation
Skin (V 1917)
Deformed Skin
Applying Mean Value Coordinates
Computing Mean Value Coordinates
Bone (V 13689)
Deformed Bone (V 13689)
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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
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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
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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

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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

i
The input model i
The distance volume
The segmentation volume
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Offset Volume

• Generate an offset volume by choosing all points
  satisfying dist(p)ltt
• 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
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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

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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.

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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

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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
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Experimental Results

• IVIS system
• 3D texture slicing number 1000
• Image resolution 480x480

Data I II III FPS
Brain 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
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Foot Deformation
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Shape-aware Volume Rendering
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Bunny Deformation
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Hand Example
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MRI Brain Data Example
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Kidney Data Example
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Conclusions

• Contributions

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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

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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.

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Thank You !
chen23_at_purdue.edu http//web.ics.purdue.edu/chen2
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Work Pipeline of Volume Illustration
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Work Pipeline of Volume Illustration
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