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Errorbounded Reduction of Triangle Meshes with Multivariate Data

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Data Courtesty Space Science and Engineering Center. Earth Science Data. Original Data (4846 tri) ... Data Courtesty Space Science and Engineering Center. Future Work ... – PowerPoint PPT presentation

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Title: Errorbounded Reduction of Triangle Meshes with Multivariate Data


1
Error-bounded Reduction of Triangle Meshes with
Multivariate Data
  • Chandrajit L. Bajaj
  • Daniel R. Schikore

2
Outline
  • Problem Definition
  • Related Work
  • Motivation
  • Outline of Algorithm
  • Results
  • Future Work

3
Problem Definition
  • Geometric surface defined by triangles
  • Multivariate data defined at vertices
  • Compute a reduced size mesh for display which
    adapts to both the geometry and the data defined

4
Related Work
  • Geometric Reduction - Point/Edge/Triangle
    Deletion (Hamann, Rossignac et al., Schroeder
    et al.) Energy Optimization (Hoppe et al.,
    Turk) Resampling (He et al.) Remeshing (Eck et
    al.)
  • Data Reduction - Point Insertion/Deletion
    (DeFloriani et al., Fowler et al., Lee, Puppo
    et. al, Silva et al., Tsai, Ware et
    al.)

5
Motivation
  • Data is often defined on surfaces
  • Existing mesh reduction methods satisfy error
    criteria in geometry or data, but not both.

6
Algorithm Outline
  • Consider each vertex v for deletion
  • Compute a triangulation of the neighbors of
    vertex v
  • Determine mapping between triangulations
  • Iteratively attempt to improve triangulation
    (reduce error) by edge-flipping
  • Delete v if error criteria are satisfied

7
Mapping Between Triangulations
  • Projection of New
  • Triangulation

Interior Vertex
8
Error Representation
  • Two error values per face - Easy to update
    - Combines information about all deleted
    vertices

9
Computing Geometric Error
  • Geometric error is quantified by the signed
    distance from the old triangulation to the new
    triangulation
  • Displacement in the direction of normal is
    positive error by convention

10
Computing Data Errors
  • Errors in data are quantified by the signed
    difference between interpolated data values in
    the old and new triangulations

11
Error Propagation
  • Projection of New
  • Triangulation

Segmentation
12
Retriangulation
  • Initial triangulation is arbitrary
  • Cost of an edge may be computed as a) Maximum
    error in geometry or data b) Maximum error
    introduced in geometry or data
  • Edges are flipped if cost of the flipped edge
    is lower than the cost of the current edge

13
Results
14
Projectile Impact
Original Data (2869 tri)
3 Error (1356 tri)
Data Courtesy Lawrence Livermore National
Laboratory
15
Projectile Impact
Original Data (2869 tri)
3 Error (1356 tri)
Data Courtesy Lawrence Livermore National
Laboratory
16
Earth Science Data
Original Data (4846 tri)
3 Error (2384 tri)
Data Courtesty Space Science and Engineering
Center
17
Earth Science Data
Original Data (4846 tri)
3 Error (2384 tri)
Data Courtesty Space Science and Engineering
Center
18
Future Work
  • Improved measures of error (Linear/ Quadratic
    fitting)
  • Better initial triangulation
  • Improved edge-flipping for optimization
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