用几何与颜色场相似性评估3D网格质量，更准更快。
Textured mesh Quality Assessment using Geometry and Color Field Similarity
- 基于符号距离场和新提出的颜色场描述网格特征
- 在三个数据集上优于现有最先进方法，且计算开销低
- 适合需要高效高精度评估的3D图形与可视化应用
纹理网格质量评估（TMQA）对多种3D网格应用至关重要。然而，现有方法常难以提供准确且鲁棒的评估。受场表示在表达3D几何与颜色信息方面的有效性启发，我们提出一种新的基于点的TMQA方法——场网格质量度量（FMQM）。FMQM利用符号距离场和一种新提出的颜色场——最近表面点颜色场，实现有效的网格特征描述。从几何与颜色场中提取了四种与视觉感知相关的特征：几何相似性、几何梯度相似性、空间颜色分布相似性和空间颜色梯度相似性。在三个基准数据集上的实验结果表明，FMQM优于当前最先进的TMQA度量方法。此外，FMQM表现出低计算复杂度，是3D图形与可视化领域实际应用中的高效解决方案。代码已公开于：https://github.com/yyyykf/FMQM。
原文摘要 · Abstract (English)
Textured mesh quality assessment (TMQA) is critical for various 3D mesh applications. However, existing TMQA methods often struggle to provide accurate and robust evaluations. Motivated by the effectiveness of fields in representing both 3D geometry and color information, we propose a novel point-based TMQA method called field mesh quality metric (FMQM). FMQM utilizes signed distance fields and a newly proposed color field named nearest surface point color field to realize effective mesh feature description. Four features related to visual perception are extracted from the geometry and color fields: geometry similarity, geometry gradient similarity, space color distribution similarity, and space color gradient similarity. Experimental results on three benchmark datasets demonstrate that FMQM outperforms state-of-the-art (SOTA) TMQA metrics. Furthermore, FMQM exhibits low computational complexity, making it a practical and efficient solution for real-world applications in 3D graphics and visualization. Our code is publicly available at: https://github.com/yyyykf/FMQM.
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