多模式人体运动数据集的3D解剖学地标和构成关键点的数据集
Ana Virginia Ruescas-Nicolau1, Enrique José Medina-Ripoll1, Eduardo Parrilla Bernabé1
1Instituto de Biomecánica - IBV, Universitat Politècnica de València, Edificio 9C. Camí de Vera s/n, 46022 Valencia, Spain.
Data in brief
|February 20, 2024
概括
这一新数据集将2D和3D人体姿势关键点与3D解剖学地标联系起来. 它可以从计算机视觉提出解决方案来开发生物机械应用.
科学领域:
- 生物机械工程 生物机械工程
- 计算机视觉 计算机视觉
- 人类运动分析分析
背景情况:
- 准确的3D人体姿势估计对于生物力学分析和模拟至关重要.
- 现有的计算机视觉姿势解决方案往往缺乏直接的解剖学里程碑对应.
- 弥合姿势估计和生物力学之间的差距需要专门的数据集.
研究的目的:
- 引入一套新的数据集,将2D/3D人体姿势关键点与3D解剖学地标联系起来.
- 为了促进计算机视觉的翻译,将图形估计转化为生物力学应用.
- 支持神经网络培训研究的人类运动分析.
主要方法:
- 创建了来自71个个体的51051个姿势的数据集,跨越7个运动.
- 创建了3D移动纹理网格,用于地标提取的解剖对应.
- 利用虚拟摄像头捕获48张图像,用MediaPipe提取2D关键点,并通过线性三角测量计算3D关键点.
主要成果:
- 数据集包括3D关键点,53个3D解剖学地标,2D关键点和相机校准参数.
- 数据按参与者进行组织,TRC和JSON文件详细说明了姿势和地标信息.
- 参与者的人类测量数据在CSV文件中提供.
结论:
- 这一数据集是将人类姿势解决方案转化为生物机械应用的宝贵资源.
- 它可以研究人类运动分析对人类测量特征的影响.
- 这些数据支持训练神经网络以进行复杂的运动分析的进展.
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