2D Video Dataset for Detailed Pose Estimation of the Running Form

The goal of pose estimation in computer vision is to detect and classify the joints of the human body to describe the pose of a person. During running, pose estimation can provide valuable insights into the running form and identify abnormalities or areas for improvement. Most existing datasets are image-based and contain at most 17 keypoints and miss important joints, such as heels and toes, which are essential for properly analysing the running form. This paper proposes a new video dataset annotated with 26 body key points to facilitate the benchmarking of pose estimation in this area and promote new opportunities for further research on the running form.