Visualization of Point-Based Surfaces with Locally Reconstructed Subdivision Surfaces - PowerPoint PPT Presentation

Title: Visualization of Point-Based Surfaces with Locally Reconstructed Subdivision Surfaces


1
Visualization of Point-Based Surfaces with
Locally Reconstructed Subdivision Surfaces

• Tamy Boubekeur
• Patrick Reuter
• Christophe Schlick
• LaBRI, LIPSI - University of Bordeaux - France

2
Point-Based Graphics

• Core unstructured point cloud
• Points with attributes
• Color
• Normal
• Etc.
• Advantages
• Acquisition
• Multiresolution
• Storage
• Drawback visualization

3
Previous work Surface Splatting

• For each point in the object space, draw a small
  circle or ellipse in the image space to obtain a
  hole-free surface.
• Surface Splatting
• Zwicker et al. 2001
• Phong Splatting
• Botsch et al. 2004
• High Quality Surface Splatting on Todays GPUs
• Botsch et al. 2005
• Drawback complete rewriting of rendering
  algorithms

4
Alternative Surface Reconstruction

• Conversion from a point cloud to an other model
  (mesh, NURBS, implicit, etc.)
• Implicit approaches MPU, RBF
• Othake et al. 2003Tobor et al. 2004
• Explicit approaches Voronoï/Delaunay
• Amenta et al. 99Dey et al. 2001
• Other approaches deformable models, direct
  parametrization, etc.
• Drawback generation time

5
Problem ?

• Handle large point clouds
• Object-space reconstruction
• Rapid visualization
• Hardware acceleration

6
Solution

• Handle large point clouds
• Object-space reconstruction
• Rapid Visualization
• Hardware acceleration

Local approach Polygonal reconstruction Trade-off
between quality and performance Standard hardware
rendering pipeline
7
Our approach

• Spatial partitioning with octree
• Local polygonal reconstruction in each partition
  overlappings between partitions
• Aggregation of the pieces of surfaces with
  subdivision

8
Our approach
Overview

• Usual bottleneck mesh generation /
  reconstruction
• Efficient local reconstruction ? constrained
  partitioning

9
Local Reconstruction

• Height-map property locally, a surface can be
  defined by z f(x,y)
• Local 2D incremental Delaunay Triangulation
• Computational complexity in O(n.log(n)) for n
  points
• More economic and faster than 3D triangulations

10
Local Reconstruction
Partition point cloud
11
Local Reconstruction
Projection onto the average plane
12
Local Reconstruction
2D Triangulation
13
Local Reconstruction
3D projection
14
Local Reconstruction
The piece of surface obtained
15
Local Reconstruction
Sudivision
16
Overlappings

• Problem holes inbetween the pieces of surfaces
• Solution
• enlarging temporarily the reconstruction support,
  by creating overlappings between neighboring
  surfaces
• Taking benefit of the partitioning structure

17
Partitioning
Level 5
Level 6

• Octree simple, adaptive, convergence toward the
  surface
• Drive the reconstruction step by providing a good
  approximation of the global topology

18
Partitioning

• Local Height Map criteria
• Normal Deviation criteria
• Geometric Deviation criteria

19
Partitioning

• Partition size criteria
• Balance complexity
• Helps to resolve a wide range of topological
  inconsistencies

20
Subdivision Surfaces

• Application to local piece of mesh piecewise C2
  continuity (C1 for extraordinary vertices)
  Loop 1987
• Eliminates artefacts in overlappings zones
  (interpolatory boundary rules)
• Modification projective Loop Scheme

21
Hardware Rendering

• No GPU programming
• Visibility tests (octree)
• Standard (OpenGL)
• Example Environnement Cube Mapping

22
High Quality Rendering

• Point cloud raytracing
• Just a ray-triangle intersection test
• lazy generation
• Huge scene rendering

23
Results
Torso 2941 pts 0.33 sec.

• Smoothing by subdivision without visual
  artefacts.

24
Results

• Visual continuity

Quasi-Delaunay mesh
AdamKraft 7073 pts 4.12 sec.
Dragon 100251 pts 4.83 sec.
25
Results
Bottle 42736 pts 2.13 sec.
Knot 28659 pts 1.40 sec.
Robust against non uniform point clouds and
complex topologies.
26
Results
27
Results
Near-linear complexity in time
28
Conclusion

• Advantages
• Local and fast approach
• Quasi-Delaunay polygonal output
• A visual continuity
• Can replace true surface reconstruction in
  various cases
• Limitations
• Very non uniform point clouds

29
Conclusion
Comparison with other approaches
30
Current/Future Work

• Surface reconstruction
• Huge data (out-of-core processing/clusters)
• Point-cloud resampling
• Improved projection rule
• Manifold extraction

31
Current/Future Works

• Visualization
• A complete polygonal approach for high-quality
  rendering of point clouds
• PointShop 3D integration

32

Thank you for your attention !

• www.labri.fr/boubek