Subjective and Objective Visual Quality Assessment of Textured 3D Meshes

• URL: http://arxiv.org/abs/2102.03982v1
• Date: Mon, 8 Feb 2021 03:26:41 GMT
• Title: Subjective and Objective Visual Quality Assessment of Textured 3D Meshes
• Authors: Jinjiang Guo, Vincent Vidal, Irene Cheng, Anup Basu, Atilla Baskurt, Guillaume Lavoue
• Abstract summary: We present a new subjective study to evaluate the perceptual quality of textured meshes, based on a paired comparison protocol. We propose two new metrics for visual quality assessment of textured mesh, as optimized linear combinations of accurate geometry and texture quality measurements.
• Score: 3.738515725866836
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Objective visual quality assessment of 3D models is a fundamental issue in computer graphics. Quality assessment metrics may allow a wide range of processes to be guided and evaluated, such as level of detail creation, compression, filtering, and so on. Most computer graphics assets are composed of geometric surfaces on which several texture images can be mapped to 11 make the rendering more realistic. While some quality assessment metrics exist for geometric surfaces, almost no research has been conducted on the evaluation of texture-mapped 3D models. In this context, we present a new subjective study to evaluate the perceptual quality of textured meshes, based on a paired comparison protocol. We introduce both texture and geometry distortions on a set of 5 reference models to produce a database of 136 distorted models, evaluated using two rendering protocols. Based on analysis of the results, we propose two new metrics for visual quality assessment of textured mesh, as optimized linear combinations of accurate geometry and texture quality measurements. These proposed perceptual metrics outperform their counterparts in terms of correlation with human opinion. The database, along with the associated subjective scores, will be made publicly available online.

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