Textured Mesh Quality Assessment Using Geometry and Color Field Similarity

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.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-09-22
DOI
https://doi.org/10.1109/tvcg.2025.3612942
Primary Topic
3D Shape Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Textured Mesh Quality Assessment Using Geometry and Color Field Similarity

Yiling Xu, Qi Yang, Zhu Li, Kaifa Yang
IEEE Transactions on Visualization and Computer Graphics
3D Shape Modeling and Analysis
article

Textured Mesh Quality Assessment Using Geometry and Color Field Similarity

Yiling Xu, Qi Yang, Zhu Li, Kaifa Yang
article en

Abstract

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.

IEEE Transactions on Visualization and Computer GraphicsVol. 31(12)
Shanghai Jiao Tong University (CN), University of Missouri–Kansas City (US)
Openalex Percentile: Top 72%
3D Shape Modeling and Analysis
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