Virtual Reality (VR) applications have revolutionized user experiences by
immersing individuals in interactive 3D environments. These environments find
applications in numerous fields, including healthcare, education, or
architecture. A significant aspect of VR is the inclusion of self-avatars,
representing users within the virtual world, which enhances interaction and
embodiment. However, generating lifelike full-body self-avatar animations
remains challenging, particularly in consumer-grade VR systems, where
lower-body tracking is often absent. One method to tackle this problem is by
providing an external source of motion information that includes lower body
information such as full Cartesian positions estimated from RGB(D) cameras.
Nevertheless, the limitations of these systems are multiples: the
desynchronization between the two motion sources and occlusions are examples of
significant issues that hinder the implementations of such systems. In this
paper, we aim to measure the impact on the reconstruction of the articulated
self-avatar's full-body pose of (1) the latency between the VR motion features
and estimated positions, (2) the data acquisition rate, (3) occlusions, and (4)
the inaccuracy of the position estimation algorithm. In addition, we analyze
the motion reconstruction errors using ground truth and 3D Cartesian
coordinates estimated from \textit{YOLOv8} pose estimation. These analyzes show
that the studied methods are significantly sensitive to any degradation tested,
especially regarding the velocity reconstruction error.

该研究探讨了虚拟现实应用中自身角色的动作信息与重建误差之间的关系，并发现方法对降解的敏感度尤其体现在动作重建速度误差。