TDMD: A Database for Dynamic Color Mesh Subjective and Objective Quality
  Explorations
Qi Yang Joel Jung Timon Deschamps Xiaozhong Xu Shan Liu
Dynamic colored meshes (DCM) are widely used in various applications;
however, these meshes may undergo different processes, such as compression or
transmission, which can distort them and degrade their quality. To facilitate
the development of objective metrics for DCMs and study the influence of
typical distortions on their perception, we create the Tencent - dynamic
colored mesh database (TDMD) containing eight reference DCM objects with six
typical distortions. Using processed video sequences (PVS) derived from the
DCM, we have conducted a large-scale subjective experiment that resulted in 303
distorted DCM samples with mean opinion scores, making the TDMD the largest
available DCM database to our knowledge. This database enabled us to study the
impact of different types of distortion on human perception and offer
recommendations for DCM compression and related tasks. Additionally, we have
evaluated three types of state-of-the-art objective metrics on the TDMD,
including image-based, point-based, and video-based metrics, on the TDMD. Our
experimental results highlight the strengths and weaknesses of each metric, and
we provide suggestions about the selection of metrics in practical DCM
applications. The TDMD will be made publicly available at the following
location: https://multimedia.tencent.com/resources/tdmd.