Preprocessing files supporting "Functional movement screen dataset collected with two Azure Kinect depth sensors"

This is preprocessing files supporting the datasets in the collection at: https://doi.org/10.25452/figshare.plus.c.5774969 This dataset supports the following publication: Xing, QJ., Shen, YY., Cao, R. et al. Functional movement screen dataset collected with two Azure Kinect depth sensors. Sci Data 9, 104 (2022). https://doi.org/10.1038/s41597-022-01188-7 Collection Description: This presents a dataset for vision-based autonomous functional movement screen (FMS) collected from 45 human subjects of different ages (18-59 years old) executing the following movements: deep squat, hurdle step, in-line lunge, shoulder mobility, active straight raise, trunk stability push-up, and rotary stability. Specifically, shoulder mobility was performed only once by different subjects, while the other movements were repeated for three episodes each. Each episode was saved as one record and was annotated from 0 to 3 by three FMS experts. The main strength of our database is twofold. One is the multimodal data provided, including color images, depth images, and 3D human skeleton joints. The other is the multiview data collected from the two synchronized Azure Kinect sensors in front of and on the side of the subjects. Finally, three-dimensional trajectories, quaternions, and 2D pixel trajectories of 32 joints were recorded. Our dataset contains a total of 1812 recordings, with 3624 episodes. The size of the dataset is 158 GB. As a supplement, we also provide color image data from the other two cameras (back and side low positions). This dataset provides the opportunity for automatic action quality evaluation of FMS.本文件为该合集内数据集的配套预处理文件，数据集获取地址：https://doi.org/10.25452/figshare.plus.c.5774969 本数据集支撑以下发表成果：Xing QJ、Shen YY、Cao R 等人的《基于两台Azure Kinect深度传感器采集的功能性动作筛查数据集》，发表于《科学数据（Sci Data）》9卷第104页（2022年），DOI：https://doi.org/10.1038/s41597-022-01188-7 数据集合集说明： 本数据集包含基于视觉的自主式功能性动作筛查（Functional Movement Screen, FMS）数据，采集自45名年龄介于18至59岁的受试者，受试者完成以下动作：深蹲、跨栏步、直线弓步、肩部活动度测试、主动直腿上抬、躯干稳定俯卧撑以及旋转稳定性测试。具体而言，肩部活动度测试仅由每位受试者完成1次，其余动作每名受试者均重复完成3组。每组动作均保存为一条记录，并由3名FMS专家按照0至3的评分标准进行标注。 本数据库的核心优势主要有两点：其一，提供多模态数据，包括彩色图像、深度图像以及三维人体骨骼关节数据；其二，采用两台同步部署的Azure Kinect传感器分别置于受试者前方与侧方采集多视角数据。此外，本数据集还记录了32个关节的三维运动轨迹、四元数数据以及二维像素坐标轨迹。 本数据集总计包含1812条记录，对应3624组动作，整体数据量达158 GB。作为补充内容，本数据集还提供了另外两台相机（分别位于受试者后方与侧下方）采集的彩色图像数据。本数据集可用于开展FMS动作质量自动评估相关研究。