This paper introduces a method for simplifying textured surface triangle meshes in the wild while maintaining high visual quality. While previous methods achieve excellent results on manifold meshes by using the quadric error metric, they struggle to produce high-quality outputs for meshes in the wild, which typically contain non-manifold elements and multiple connected components. In this work, we propose a method for simplifying these wild textured triangle meshes. We formulate mesh simplification as a problem of decimating simplicial 2-complexes to handle multiple non-manifold mesh components collectively. Building on the success of quadric error simplification, we iteratively collapse 1-simplices (vertex pairs). Our approach employs a modified quadric error that converges to the original quadric error metric for watertight manifold meshes, while significantly improving the results on wild meshes. For textures, instead of following existing strategies to preserve UVs, we adopt a novel perspective which focuses on computing mesh correspondences throughout the decimation, independent of the UV layout. This combination yields a textured mesh simplification system that is capable of handling arbitrary triangle meshes, achieving to high-quality results on wild inputs without sacrificing the excellent performance on clean inputs. Our method guarantees to avoid common problems in textured mesh simplification, including the prevalent problem of texture bleeding. We extensively evaluate our method on multiple datasets, showing improvements over prior techniques through qualitative, quantitative, and user study evaluations.
翻译:本文提出了一种简化野外纹理表面三角形网格的方法,同时保持高视觉质量。尽管先前方法通过使用二次误差度量在流形网格上取得了优异结果,但它们难以对野外网格(通常包含非流形元素和多个连通分量)生成高质量输出。本工作提出了一种简化这类野外纹理三角形网格的方法。我们将网格简化表述为对单纯2-复形进行约简的问题,以整体处理多个非流形网格分量。基于二次误差简化方法的成功经验,我们通过迭代折叠1-单纯形(顶点对)来实现简化。本方法采用改进的二次误差度量——该度量对水密流形网格收敛于原始二次误差度量,同时显著提升了野外网格的处理效果。针对纹理处理,我们摒弃了现有保留UV参数的策略,转而采用一种新颖视角:重点关注在约简过程中计算网格对应关系,使其独立于UV布局。这种组合产生了一个能够处理任意三角形网格的纹理网格简化系统,在保持对规整输入优异性能的同时,实现了对野外输入的高质量处理。本方法可保证避免纹理网格简化中的常见问题,包括普遍存在的纹理渗色现象。我们在多个数据集上对本方法进行了广泛评估,通过定性、定量和用户研究评估证明了其相对于现有技术的改进。