论文标题
HSC4D：使用可穿戴的IMU和LIDAR在大规模室内室外空间中以人为本的4D场景捕获
HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR
论文作者
论文摘要
我们建议以人为本的4D场景捕获（HSC4D）准确有效地创建一个动态的数字世界，其中包含大型室内室外场景，多样化的人类运动以及人类与环境之间的丰富互动。 HSC4D仅使用车身安装的IMU和LIDAR，没有任何外部设备的限制和无图形地图，没有预构建的地图。考虑到IMU可以捕获人类的姿势，但始终以长期使用，而LiDAR对于全球定位稳定，但对于局部位置和方向而言是粗糙的，HSC4D使这两个传感器都通过联合优化和实现长期捕获的有希望的结果相互补充。还探索了人与环境之间的关系，以使其相互作用更加现实。为了促进许多下游任务，例如AR，VR，机器人，自动驾驶等，我们提出了一个数据集，其中包含三个大型场景（1k-5k $ m^2 $），并具有准确的动态人类动作和位置。各种场景（攀岩体育馆，多层建筑，坡度等）以及挑战人类活动（锻炼，上下楼梯，攀岩等）展示了HSC4D的有效性和概括能力。该数据集和代码可在http://www.lidarhumanmotion.net/hsc4d/上找到。
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 http://www.lidarhumanmotion.net/hsc4d/.
