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技术开展人体形态研究时，常因多种误差源而面临诸多难题。与之相比，三维（3D）模型与表征方式能够实现更为精准的配准，该配准在多次采集过程中均可保持稳定，同时可支持更精准、系统化且快速的测量能力。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异测量。 本研究推出了3DPatBody数据集，该数据集包含巴塔哥尼亚人群样本的三维人体扫描模型、对应的三维点云数据以及人体测量学指标，样本构成如下：女性211例、男性87例、其他性别1例。该样本具有重要科研价值，其代表的表型兼具双重意义：既是超重与肥胖状态的生物医学描述指标，同时又具备与族群血统及/或当地环境因素相关的人群特异性特征。 本研究利用所获取的三维模型，将形态变量与传统人体测量学数据进行对比分析。研究结果表明，形态指标可作为传统人体测量指数的精准预测因子，同时还补充了更准确反映本次研究中人体形态的几何特征。