Best and practical watermarking schemes for copyright protection of 3D meshes are required to be blind and robust to attacks and errors. In this paper, we present the latest developments in 3D blind watermarking with a special emphasis on our Ordered Statistics Vertex Extraction and Tracing Algorithm (OSVETA) algorithm and its improvements. OSVETA is based on a combination of quantization index modulation (QIM) and error correction coding using novel ways for judicial selection of mesh vertices which are stable under mesh simplification, and the technique we propose in this paper offers a systematic method for vertex selection based on neural networks replacing a heuristic approach in the OSVETA. The Neuro-OSVETA enables a more precise mesh geometry estimation and better curvature and topological feature estimation. These enhancements result in a more accurate identification of stable vertices resulting in significant reduction of deletion probability.

翻译：最优秀且实用的三维网格版权保护水印方案需要具备盲检测性并对攻击和错误具有鲁棒性。本文重点介绍我们提出的有序统计顶点提取与追踪算法及其改进，展示了三维盲水印技术的最新进展。OSVETA基于量化索引调制与纠错编码的结合，采用创新方法对网格简化下保持稳定的顶点进行司法选择，而本文提出的技术则提供了基于神经网络的系统性顶点选择方法，替代了OSVETA中的启发式方法。Neuro-OSVETA实现了更精准的网格几何估计，并改善了曲率与拓扑特征估计能力。这些改进使得稳定顶点的识别更加精确，从而显著降低了误删除概率。