3DPatBody: 3D dataset of human bodies of a patagonian population and their anthropometric measurements

The study of human body shape using classical anthropometric techniques is often problematic due to several error sources.
Instead, 3D models and representations provide more accurate registrations, which are stable across acquisitions, and enable more precise, systematic, and fast measuring capabilities.
Thus, the same person can be scanned several times and precise differential measurements can be established in an accurate manner.
Here we present {\tt 3DPatBody}, a dataset including 3D body scans, with their corresponding 3D point clouds and anthropometric measurements, from a sample of a Patagonian population (female=211, male=87, other=1). The sample is of scientific interest since it is representative of a phenotype characterized by both its biomedical meaning as a descriptor of overweight and obesity, and its population-specific nature related to ancestry and/or local environmental factors. The acquired 3D models were used to compare shape variables against classical anthropometric data. The shape indicators proved to be accurate predictors of classical indices, also adding geometric characteristics that reflect more properly the shape of the body under study.

采用传统人体测量学（anthropometric）技术开展人体形态研究时，常因多种误差源的存在而难以保证结果可靠。与之相比，三维模型及表征可实现更精准的配准，该配准在多次扫描采集过程中保持稳定，同时支持更精准、系统化且高效的测量能力。因此，可对同一受试者进行多次扫描，并以高精度方式开展精准的差分测量。本研究发布3DPatBody数据集：该数据集涵盖巴塔哥尼亚人群样本的三维人体扫描模型、对应三维点云及人体测量学数据，其中女性受试者211名、男性87名、其他性别1名。该样本具有重要科研价值：其代表的表型兼具双重特征，一方面可作为超重与肥胖的生物医学表征，另一方面具备与祖先背景及/或当地环境因素相关的人群特异性。研究所获取的三维模型被用于对比形态变量与传统人体测量学数据。研究结果表明，形态指标可精准预测传统人体测量指数，同时还补充了能更准确反映研究对象人体形态的几何特征。