摘要：this paper presents a dataset for vision-based autonomous Functional Movement Screen (FMS) collected from 45 human subjects of diferent 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. Specifcally, shoulder mobility was performed only once by diferent 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, quaternions, 3D human skeleton joints and 2D pixel trajectories of 32 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, our dataset contains a total of 1812 recordings, with 3624 episodes . The size of the dataset is 190 GB . This dataset provides the opportunity for automatic action quality evaluation of FMS .
