CVFeb 8, 2021

Subjective and Objective Visual Quality Assessment of Textured 3D Meshes

arXiv:2102.03982v178 citations
Originality Incremental advance
AI Analysis

This work provides new metrics for evaluating the visual quality of textured 3D meshes, which is a problem for computer graphics professionals involved in processes like level of detail creation, compression, and filtering. This is an incremental contribution.

This paper addresses the lack of quality assessment metrics for texture-mapped 3D models by conducting a new subjective study using a paired comparison protocol. They created a database of 136 distorted models from 5 reference models and, based on the results, proposed two new perceptual metrics that are optimized linear combinations of geometry and texture quality measurements, outperforming existing counterparts in correlation with human opinion.

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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