With the rapid development of high-resolution 3D vision applications, the traditional way of manipulating surface detail requires considerable memory and computing time. To address these problems, we introduce an efficient surface detail processing framework in 2D normal domain, which extracts new normal feature representations as the carrier of micro geometry structures that are illustrated both theoretically and empirically in this article. Compared with the existing state of the arts, we verify and demonstrate that the proposed normal-based representation has three important properties, including detail separability, detail transferability and detail idempotence. Finally, three new schemes are further designed for geometric surface detail processing applications, including geometric texture synthesis, geometry detail transfer, and 3D surface super-resolution. Theoretical analysis and experimental results on the latest benchmark dataset verify the effectiveness and versatility of our normal-based representation, which accepts 30 times of the input surface vertices but at the same time only takes 6.5% memory cost and 14.0% running time in comparison with existing competing algorithms.

翻译：随着高分辨率三维视觉应用的快速发展，传统曲面细节处理方式需要大量的内存和计算时间。为解决这些问题，本文在二维法向域中引入了一种高效的曲面细节处理框架，提取新的法向特征表示作为微几何结构的载体，并从理论和实验两方面进行了阐述。与现有最先进技术相比，我们验证并证明了所提出的基于法向的表示具有三种重要特性，包括细节可分离性、细节可迁移性和细节幂等性。最后，进一步设计了三种面向几何曲面细节处理应用的新方案，包括几何纹理合成、几何细节迁移和三维曲面超分辨率。理论分析和在最新基准数据集上的实验结果证明了我们基于法向表示的有效性和通用性，与现有竞争算法相比，该方法可处理30倍的输入曲面顶点，同时仅需6.5%的内存开销和14.0%的运行时间。