We propose Human-centered 4D Scene Capture (HSC4D) to accurately and
efficiently create a dynamic digital world, containing large-scale
indoor-outdoor scenes, diverse human motions, and rich interactions between
humans and environments. Using only body-mounted IMUs and LiDAR, HSC4D is
space-free without any external devices' constraints and map-free without
pre-built maps. Considering that IMUs can capture human poses but always drift
for long-period use, while LiDAR is stable for global localization but rough
for local positions and orientations, HSC4D makes both sensors complement each
other by a joint optimization and achieves promising results for long-term
capture. Relationships between humans and environments are also explored to
make their interaction more realistic. To facilitate many down-stream tasks,
like AR, VR, robots, autonomous driving, etc., we propose a dataset containing
three large scenes (1k-5k $m^2$) with accurate dynamic human motions and
locations. Diverse scenarios (climbing gym, multi-story building, slope, etc.)
and challenging human activities (exercising, walking up/down stairs, climbing,
etc.) demonstrate the effectiveness and the generalization ability of HSC4D.
The dataset and code are available at this http URL.

提出了人性化的 4D 场景捕捉（HSC4D），使用 IMUs 和 LiDAR 进行全空间和无地图的动态数字世界创建，并将它们用于长期捕捉。同时，关注人与环境之间的关系，以实现交互更为真实。提出了一个包含准确动态人体运动和位置的大型场景数据集，可用于多个下游任务。