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Related Experiment Videos

Mesh simplification with hierarchical shape analysis and iterative edge contraction.

Jingqi Yan1, Pengfei Shi, David Zhang

  • 1Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, China. jqyan@sjtu.edu.cn

IEEE Transactions on Visualization and Computer Graphics
|September 24, 2004
PubMed
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This study introduces a new surface mesh simplification algorithm. It uses a two-phase approach for efficient shape analysis and edge contraction, improving mesh quality.

Area of Science:

  • Computer Graphics
  • Computational Geometry
  • Geometric Modeling

Background:

  • Surface mesh simplification is crucial for efficient rendering and processing of 3D models.
  • Existing algorithms often struggle to balance simplification accuracy with computational cost.
  • Hierarchical approaches offer potential for improved control over simplification.

Purpose of the Study:

  • To present a novel mesh simplification algorithm that decouples shape analysis and edge contraction.
  • To introduce a hierarchical structure for surface meshes to guide the simplification process.
  • To achieve competitive simplification results with enhanced efficiency and accuracy.

Main Methods:

  • Imposing a hierarchical structure via uniform partitioning and marking vertex importance.

Related Experiment Videos

  • Determining affected regions for each vertex at different hierarchical levels.
  • Employing a two-step contraction phase: half-edge contraction and vertex repositioning optimization.
  • Combining memoryless quadric metric error with hierarchical vertex importance for contraction.
  • Minimizing multilevel synthesized quadric error for local and global optimization.

    • Main Results:

    • The algorithm successfully imposes a hierarchical structure on surface meshes.
    • Vertex importance and affected regions are effectively determined within the hierarchy.
    • The two-phase simplification process, including half-edge contraction and optimization, yields efficient results.
    • Experimental results demonstrate competitive performance compared to existing methods.

    Conclusions:

    • The proposed mesh simplification algorithm offers a novel and effective approach.
    • Decoupling simplification into shape analysis and edge contraction enhances control and accuracy.
    • The hierarchical structure and multilevel optimization contribute to superior results.