TSMD: A Database for Static Color Mesh Quality Assessment Study

TL;DR

This paper introduces TSMD, a comprehensive dataset of static textured meshes with subjective quality scores, to advance research in mesh compression and quality assessment.

Contribution

The paper presents TSMD, a new large-scale dataset with diverse static textured meshes, subjective scores, and evaluation of objective metrics, facilitating progress in mesh quality assessment.

Findings

Objective metrics show around 0.75 correlation with subjective scores.

The dataset is validated for diversity and reliability.

Current metrics deviate from typical results on less heterogeneous data.

Abstract

Static meshes with texture map are widely used in modern industrial and manufacturing sectors, attracting considerable attention in the mesh compression community due to its huge amount of data. To facilitate the study of static mesh compression algorithm and objective quality metric, we create the Tencent - Static Mesh Dataset (TSMD) containing 42 reference meshes with rich visual characteristics. 210 distorted samples are generated by the lossy compression scheme developed for the Call for Proposals on polygonal static mesh coding, released on June 23 by the Alliance for Open Media Volumetric Visual Media group. Using processed video sequences, a large-scale, crowdsourcing-based, subjective experiment was conducted to collect subjective scores from 74 viewers. The dataset undergoes analysis to validate its sample diversity and Mean Opinion Scores (MOS) accuracy, establishing its heterogeneous nature and reliability. State-of-the-art objective metrics are evaluated on the new dataset. Pearson and Spearman correlations around 0.75 are reported, deviating from results typically observed on less heterogeneous datasets, demonstrating the need for further development of more robust metrics. The TSMD, including meshes, PVSs, bitstreams, and MOS, is made publicly available at the following location: https://multimedia.tencent.com/resources/tsmd.