arXiv:2510.22646eess.IVcs.MM2025-10

通过分阶段生成锚网格,高效压缩动态网格并保持拓扑一致。

TVMC: Time-Varying Mesh Compression via Multi-Stage Anchor Mesh Generation

  • 分三阶段构建锚网格:快速对齐、运动补偿、几何优化。
  • 相比最新标准V-DMC,码率降低10.2%~16.9%,重建质量高。
  • 适合需要高质量动态网格压缩的增强现实应用。

时变网格具有动态连接性和变化的顶点数量,在增强现实等应用中前景广阔。然而,其高保真表示所需的数据量巨大,实际应用受限。现有压缩方法虽尝试利用帧间时间冗余,但普遍面临拓扑不一致和运动引起的伪影问题。为此,本文提出时间变网格压缩(TVMC)框架,基于多阶段粗到细的锚网格生成实现帧间预测。锚网格分三步构建:初始阶段通过快速拓扑对齐利用时间相干性;卡尔曼滤波运动估计模块生成粗锚网格以精确补偿帧间运动;最后基于四边形误差度量优化顶点位置,形成几何保真度更高的细锚网格。基于此精细锚网格,编码相对于参考基网格的帧间运动,并自适应量化与压缩细分后的细锚网格与输入网格间的残差位移。该分层策略在保持连贯拓扑与高质量表面近似的同时,实现了高效的动态几何紧凑表示。在标准MPEG动态网格序列上的大量实验表明,TVMC达到当前最优压缩性能,相比最新V-DMC标准,实现10.2%~16.9%的显著BD-rate增益,同时保持高重建质量。代码已开源。

原文摘要 · Abstract (English)

Time-varying meshes, characterized by dynamic connectivity and varying vertex counts, hold significant promise for applications such as augmented reality. However, their practical utilization remains challenging due to the substantial data volume required for high-fidelity representation. While various compression methods attempt to leverage temporal redundancy between consecutive mesh frames, most struggle with topological inconsistency and motion-induced artifacts. To address these issues, we propose Time-Varying Mesh Compression (TVMC), a novel framework built on multi-stage coarse-to-fine anchor mesh generation for inter-frame prediction. Specifically, the anchor mesh is progressively constructed in three stages: initial, coarse, and fine. The initial anchor mesh is obtained through fast topology alignment to exploit temporal coherence. A Kalman filter-based motion estimation module then generates a coarse anchor mesh by accurately compensating inter-frame motions. Subsequently, a Quadric Error Metric-based refinement step optimizes vertex positions to form a fine anchor mesh with improved geometric fidelity. Based on the refined anchor mesh, the inter-frame motions relative to the reference base mesh are encoded, while the residual displacements between the subdivided fine anchor mesh and the input mesh are adaptively quantized and compressed. This hierarchical strategy preserves consistent connectivity and high-quality surface approximation, while achieving an efficient and compact representation of dynamic geometry. Extensive experiments on standard MPEG dynamic mesh sequences demonstrate that TVMC achieves state-of-the-art compression performance. Compared to the latest V-DMC standard, it delivers a significant BD-rate gain of 10.2% ~ 16.9%, while preserving high reconstruction quality. The code is available at https://github.com/H-Huang774/TVMC.

网格压缩动态网格锚网格增强现实

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