Textured mesh Quality Assessment using Geometry and Color Field Similarity

TL;DR

This paper introduces FMQM, a novel point-based textured mesh quality assessment method utilizing geometry and color fields, which outperforms existing metrics in accuracy and efficiency for 3D mesh evaluation.

Contribution

The paper proposes a new TMQA approach using signed distance and color fields, providing more accurate and computationally efficient mesh quality evaluation.

Findings

FMQM outperforms state-of-the-art TMQA metrics.

FMQM has low computational complexity.

Experimental results validate FMQM's effectiveness.

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. Our code is publicly available at: https://github.com/yyyykf/FMQM.