Mixed reality applications require tracking the user's full-body motion to
enable an immersive experience. However, typical head-mounted devices can only
track head and hand movements, leading to a limited reconstruction of full-body
motion due to variability in lower body configurations. We propose BoDiffusion
-- a generative diffusion model for motion synthesis to tackle this
under-constrained reconstruction problem. We present a time and space
conditioning scheme that allows BoDiffusion to leverage sparse tracking inputs
while generating smooth and realistic full-body motion sequences. To the best
of our knowledge, this is the first approach that uses the reverse diffusion
process to model full-body tracking as a conditional sequence generation task.
We conduct experiments on the large-scale motion-capture dataset AMASS and show
that our approach outperforms the state-of-the-art approaches by a significant
margin in terms of full-body motion realism and joint reconstruction error.

本研究提出了一种名为 BoDiffusion 的生成扩散模型，用于解决头戴式设备只能追踪头部和手部运动的局限，通过条件序列生成任务模拟全身运动，实验表明该模型在运动合成方面的性能优于现有模型。

BoDiffusion：用于全身人体运动合成的稀疏观测扩散

BoDiffusion: Diffusing Sparse Observations for Full-Body Human Motion  Synthesis

Current motion capture (MoCap) systems generally require markers and multiple
calibrated cameras, which can be used only in constrained environments. In this
work we introduce a drone-based system for 3D human MoCap. The system only
needs an autonomously flying drone with an on-board RGB camera and is usable in
various indoor and outdoor environments. A reconstruction algorithm is
developed to recover full-body motion from the video recorded by the drone. We
argue that, besides the capability of tracking a moving subject, a flying drone
also provides fast varying viewpoints, which is beneficial for motion
reconstruction. We evaluate the accuracy of the proposed system using our new
DroCap dataset and also demonstrate its applicability for MoCap in the wild
using a consumer drone.

本篇论文介绍一种基于无人机的运动捕捉系统，该系统利用机载 RGB 相机可以在各种室内和室外环境中进行使用，采用重构算法从无人机拍摄的视频中恢复全身运动，同时评估了该系统的准确性及其在消费无人机中的实用性。