Subjective and Objective Visual Quality Assessment of Textured 3D Meshes
Jinjiang Guo, Vincent Vidal, Irene Cheng, Anup Basu, Atilla Baskurt,, Guillaume Lavoue

TL;DR
This paper introduces a new subjective study and two novel metrics for assessing the visual quality of textured 3D meshes, outperforming existing methods in correlating with human perception.
Contribution
It presents the first comprehensive subjective evaluation of textured 3D meshes and proposes new perceptual quality metrics combining geometry and texture assessments.
Findings
Proposed metrics outperform existing ones in correlation with human opinion.
Created a publicly available database of textured 3D meshes with subjective scores.
Validated the effectiveness of combined geometry and texture quality measurements.
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…
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