Trujillo-Jiménez Magda Alexandra, Morales Leonardo, Pazos Bruno, Ramallo Virginia, Paschetta Carolina, Azevedo Soledad De, Ruderman Anahí, Pérez Luis Orlando, Teodoroff Tamara, Delrieux Claudio, González-José Rolando
Laboratorio de Ciencias de las Imágenes, Departamento de Ingeniería Eléctrica y Computadoras, Universidad Nacional del Sur and CONICET, Bahía Blanca, B8000, Argentina.
Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9120, Argentina.
Sci Data. 2024 Dec 18;11(1):1360. doi: 10.1038/s41597-024-04189-w.
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 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.
由于存在多种误差来源,使用经典人体测量技术研究人体形状往往存在问题。相反,三维模型和表示提供了更准确的配准,在多次采集过程中保持稳定,并具备更精确、系统和快速的测量能力。因此,可以对同一个人进行多次扫描,并以准确的方式建立精确的差异测量。在此,我们展示了3DPatBody数据集,它包含来自巴塔哥尼亚人群样本(女性 = 211人,男性 = 87人,其他 = 1人)的三维人体扫描数据及其相应的三维点云数据和人体测量数据。该样本具有科学研究价值,因为它代表了一种表型,既具有作为超重和肥胖描述符的生物医学意义,又具有与祖先和/或当地环境因素相关的特定人群特征。所获取的三维模型用于将形状变量与经典人体测量数据进行比较。结果表明,形状指标是经典指标的准确预测因子,还增加了能更恰当地反映所研究人体形状的几何特征。