The SportsPose dataset

SportsPose is a large-scale 3D human pose dataset consisting of highly dynamic sports movements. With more than 176.000 3D poses from 24 different subjects performing 5 different sports activities filmed from 7 different points of view, SportsPose provides a diverse and comprehensive set of 3D poses that reflect the complex and dynamic nature of sports movements. The precision of SportsPose has been quantitatively evaluated by comparing our poses with a commercial marker-based system, achieving a mean error of 34.5 mm across all evaluation sequences. We hope that SportsPose will allow researchers and practitioners to develop and evaluate more effective models for the analysis of sports performance and injury prevention and for advancing the state-of-the-art in pose estimation in sports.For additional information regarding the dataset and accompanying code, kindly refer to the project webpage: https://christianingwersen.github.io/SportsPose/The dataset is intended for academic use only, and access is granted by request. The data is licensed under a custom academic license. For more information, see the 'data' page on the project webpage.SportsPose是一款大规模三维人体姿态数据集（3D human pose dataset），收录了来自24名不同受试者完成5类体育运动时的超过17.6万个三维姿态数据，所有数据均通过7种不同拍摄视角采集，可提供丰富且全面的三维姿态集合，精准反映体育运动动作复杂且动态的固有属性。研究团队通过将本数据集的姿态数据与商用基于标记点的动作捕捉系统（commercial marker-based system）进行对标验证，对SportsPose的精度开展了定量评估，所有评估序列的平均误差仅为34.5毫米。我们期望SportsPose能够助力科研人员与行业从业者开发并评估更高效的模型，可应用于运动表现分析、运动损伤预防研究，以及推动体育领域姿态估计技术的前沿发展。如需了解该数据集与配套代码的更多详情，请访问项目官方网页：https://christianingwersen.github.io/SportsPose/。本数据集仅可用于学术研究用途，需通过申请方可获取，数据采用定制化学术许可协议进行授权，相关许可细节可参阅项目网页中的「数据」页面。