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Related Experiment Videos

Adaptive geometry image.

Chih-Yuan Yao1, Tong-Yee Lee

  • 1Computer Graphics Group/Visual System Laboratory, Department of Computer Science and Information Engineering, National Cheng-Kung University, Tainan, Taiwan, R.O.C. ippo@csie.ncku.edu.tw

IEEE Transactions on Visualization and Computer Graphics
|May 10, 2008
PubMed
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Adaptive Geometry Images (AGIM) enhance 3D surface parameterization by reducing reconstruction errors. This novel technique improves upon existing methods, offering significant gains in Peak Signal-to-Noise Ratio (PSNR) for global parameterization.

Area of Science:

  • Computer Graphics
  • Geometric Modeling
  • Image Processing

Background:

  • Global parameterization techniques embed 3D surfaces into 2D domains.
  • Existing methods like Geometry Images (GIMs) can suffer from undersampling and reconstruction errors.
  • T-vertices in parameterizations can lead to cracks between adjacent surface patches.

Purpose of the Study:

  • Introduce Adaptive Geometry Images (AGIM) as a post-processing utility for global parameterization.
  • Address and reduce local reconstruction errors in 3D surface parameterization.
  • Improve the quality and efficiency of embedding 3D surfaces onto rectangular domains.

Main Methods:

  • Convert a single rectangular parameterization into multiple tessellations of square Geometry Images (GIMs).

Related Experiment Videos

  • Efficiently pack these GIMs into a single Adaptive Geometry Image (AGIM).
  • Dynamically compute and modify AGIM connectivity at rendering time, avoiding T-vertices.

    • Main Results:

    • AGIM achieves significant Peak Signal-to-Noise Ratio (PSNR) gains over input parameterizations.
    • Reduces reconstruction errors compared to the original GIM technique.
    • PolyCube-based quadrilateral complexes with AGIM outperform state-of-the-art multichart GIM in PSNR.

    Conclusions:

    • AGIM is an effective post-processing technique for global parameterization.
    • Eliminates cracks by avoiding T-vertices, improving surface representation.
    • Enhances the quality of 3D surface parameterization, particularly for quadrilateral complexes.