relief: a modeling by drawing tool
DESCRIPTION
This paper presents a modeling system which takes advantage of two-dimensional drawing knowledge to design three-dimensional free-form shapes. A set of mouse or tablet strokes is interpreted by the system as defining both a two-dimensional shape boundary and a displacement map. This information is used for pushing or pulling vertices of existing surfaces, or for creating vertices of new surface patches. To relieve the burden of 3D manipulation from the user, patches are automatically positioned in space. The iterative design process alternates a modeling by drawing sequence and a viewpoint change. To stay as close as possible to the traditional drawing experience, the system imposes the minimum number of constraints on the topology of either the strokes set or the resulting surface.TRANSCRIPT
Relief: A Modeling by Drawing Tool
David Bourguignon1 Raphaëlle Chaine2
Marie-Paule Cani3 George Drettakis4
1Princeton University / INRIA Rocquencourt 2LIRIS / CNRS / UCBL3GRAVIR / INP Grenoble 4REVES / INRIA Sophia-Antipolis
Outline
• Motivation• Previous Work• Tool Workflow• Reconstruction• Adaptive Sampling & Depth Inference• Tool Interface• Results
On Users
• Most people draw– Writing alternative
• Few people sculpt– Play-Doh days long gone– Materials difficult to handle
Goals
• Use 2D tools to perform 3D operations
Goals
• Use 2D tools to perform 3D operations• Model global and local surface
Goals
• Use 2D tools to perform 3D operations• Model global and local surface• Input: just plain strokes
Goals
• Use 2D tools to perform 3D operations• Model global and local surface• Input: just plain strokes• Output: triangle mesh
Outline
• Motivations• Previous Work• Tool Workflow• Reconstruction• Adaptive Sampling & Depth Inference• Tool Interface• Results
Previous Work
• Depth painting [Williams, 1990]
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Previous Work
• Gradient editing [van Overveld, 1996]
Previous Work
• Maya 6.0 Artisan [Alias, 2004]
Outline
• Motivations• Previous Work• Tool Workflow• Reconstruction• Adaptive Sampling & Depth Inference• Tool Interface• Results
Tool Workflow
• First step: drawing input– Displacement map
• mid-grey = 0• white > 0• black < 0
Model of 3D sphere
Pencil
Brush
Tool Workflow
• First step: drawing– Displacement map– 2D shape boundary
(in green)• defines drawing mask
Tool Workflow
• First step: drawing– Displacement map– 2D shape boundary– Displacement regions (from 2 maps)
Tool Workflow
• Second step: modeling– Displace existing vertices
Tool Workflow
• Second step: modeling– Displace existing vertices– Create new surface patch
Tool Workflow
• Changing viewpoint
Modeling by drawing
Changing viewpoint
Reconstruction
• Based on evolving pseudo-manifold [Chaine, 2003]
Reconstruction
• Based on evolving pseudo-manifold [Chaine, 2003]
• Satisfy our requirements– Arbitrary number of connected components
Reconstruction
• Based on evolving pseudo-manifold [Chaine, 2003]
• Satisfy our requirements– Arbitrary number of connected components– Handle points off shape boundary
Reconstruction
• Based on evolving pseudo-manifold [Chaine, 2003]
• Satisfy our requirements– Arbitrary number of connected components– Handle points off shape boundary– Interactive (5k points per second)
2D reconstruction
• Start: pseudo-curve lies on oriented edges of Delaunay triangulation
2D reconstruction
• During: pseudo-curve evolves as long as oriented Gabriel criterion is not met
2D reconstruction
• Stop: topologically consistent set of oriented edges
Sampling and Depth
• Adaptive sampling– Displacement map
• Pencil and brush datain color buffer
Color buffer
Sampling and Depth
• Adaptive sampling– Displacement map– Approximate disp. map
sampled at existing vertices
Sampling and Depth
• Adaptive sampling– Displacement map (D)– Vertex-Sampled disp.
map (V)– Error map
E = 1 – ABS(D – V)– Arbitrary error value
Sampling and Depth
• Adaptive sampling– Displacement map– Approximate disp. map– Error map– Sampling [Alliez, 2002]
Sampling and Depth
• Adaptive sampling• Depth inference
– Identify surface vertices
Vertices ID buffer
Sampling and Depth
• Adaptive sampling• Depth inference
– Identify surface vertices– Assign depth values
Depth buffer
Sampling and Depth
• Adaptive sampling• Depth inference
– Identify surface vertices– Assign depth values– Infer depth values
• from existing surface• by depth propagation
Outline
• Motivations• Previous Work• Tool Workflow• Reconstruction• Adaptive Sampling & Depth Inference• Tool Interface• Results
Tool Interface
• Hole marks– Comic books production
Hole marks
Stone #3 (Avalon Studios)
Tool Interface
• Hole marks– Comic books production– Our system
Hole mark
Tool Interface
• Video: Basic interface
Tool Interface
• Blobbing
Drawing White shadingDistance field Height field Surface
Tool Interface
• Depth modes (chosen by menu)
Modeling “at depth”Depth inference Frisket mode
Video
• Modeling a tree
Paper sketch 3D model obtained with Relief
Outline
• Motivations• Previous Work• Tool Workflow• Reconstruction• Adaptive Sampling & Depth Inference• Tool Interface• Results
Results
• Models (1k to 4k points)
Discussion
• Intuitive shading convention
Discussion
• Intuitive shading convention• Problems with drawing metaphor
– No continuous visual feedback• Provide two modes
Discussion
• Intuitive shading convention• Problems with drawing metaphor
– No continuous visual feedback– Difficult to obtain continuous shading
• Provide higher-level drawing tools
Conclusion
• Modeling by drawing, but imprecise
Conclusion
• Modeling by drawing, but imprecise• Future work
– Speedup with local 3D reconstruction
Conclusion
• Modeling by drawing, but imprecise• Future work
– Speedup with local 3D reconstruction– Improve depth inference
Conclusion
• Modeling by drawing, but imprecise• Future work
– Speedup with local 3D reconstruction– Improve depth inference– Image-space and object-space sampling
Acknowledgements
This work has been performed while the first author was a visiting research fellow at Princeton University, supported by an INRIA post-doctoral fellowship.
Many people have indirectly contributed to it. We would like to thank: Adam Finkelstein, Szymon Rusinkiewicz, Jason Lawrence, Pierre Alliez, Mariette Yvinec, Laurence Boissieux, Laure Heïgéas, Laks Raghupathi, Olivier Cuisenaire, Bingfeng Zhou.