  Fuelled by the increase in popularity of virtual and augmented reality
applications, point clouds have emerged as a popular 3D format for acquisition
and rendering of digital humans, thanks to their versatility and real-time
capabilities. Due to technological constraints and real-time rendering
limitations, however, the visual quality of dynamic point cloud contents is
seldom evaluated using virtual and augmented reality devices, instead relying
on prerecorded videos displayed on conventional 2D screens. In this study, we
evaluate how the visual quality of point clouds representing digital humans is
affected by compression distortions. In particular, we compare three different
viewing conditions based on the degrees of freedom that are granted to the
viewer: passive viewing (2DTV), head rotation (3DoF), and rotation and
translation (6DoF), to understand how interacting in the virtual space affects
the perception of quality. We provide both quantitative and qualitative results
of our evaluation involving 78 participants, and we make the data publicly
available. To the best of our knowledge, this is the first study evaluating the
quality of dynamic point clouds in virtual reality, and comparing it to
traditional viewing settings. Results highlight the dependency of visual
quality on the content under test, and limitations in the way current data sets
are used to evaluate compression solutions. Moreover, influencing factors in
quality evaluation in VR, and shortcomings in how point cloud encoding
solutions handle visually-lossless compression, are discussed.
