The geometry image representation is a remeshing of an irregular triangle surface mesh onto a rectangular grid of points and facilitates the processing of surface geometry. Its connectivity is commonly generated by splitting each rectangular quad of grid points along the shorter diagonal. However, this simple approach typically yields skinny triangles on the surface when the underlying local surface metric tensor eigenvalues differ significantly. Sequences of such triangles can appear like jaggedness.

This paper presents a greedy, region growing algorithm for anisotropic triangulation of geometry images obtained by geometric stretch parametrization. The algorithm compensates for the local stretch anisotropy and variations in the principal directions of the metric tensor by minimizing the total length of the new edges of triangles added to the grown region. The surface reconstructed is more faithful to the original surface than the ones reconstructed by quad-splitting connectivity and recognized triangulation approaches for point clouds.

几何图像表示是将不规则的三角形表面网格刷新到点的矩形网格上，并有助于处理表面几何形状。它的连通性通常是通过沿较短的对角线拆分网格点的每个矩形四边形来生成的。但是，当基础局部表面度量张量特征值显着不同时，这种简单方法通常会在表面上生成细三角形。这种三角形的序列可能看起来像锯齿状。

本文提出了一种贪婪的区域增长算法，用于通过几何拉伸参数化获得的几何图像的各向异性三角剖分。该算法通过最小化添加到生长区域的三角形的新边的总长度，来补偿局部拉伸各向异性和度量张量的主方向​​上的变化。与通过四分割连接和公认的点云三角剖分方法重建的表面相比，重建的表面更忠实于原始表面。