Total and regional body composition are important indicators of health and mortality risk, but their measurement is usually restricted to controlled environments in clinical settings with expensive and specialized equipment. A method that approaches the accuracy of the current gold standard method, dual‐energy x‐ray absorptiometry (DXA), while only requiring input from widely available consumer grade equipment, would enable the measurement of these important biometrics in the wild, enabling data collection at a scale that would have previously been prohibitive in time and expense. We describe an algorithm for predicting three‐dimensional (3D) body shape and composition from a single frontal 2‐dimensional image acquired with a digital consumer camera.

中文翻译：

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从传统的 2D 摄影中预测 3D 体型和身体成分

总体和区域身体成分是健康和死亡风险的重要指标，但它们的测量通常仅限于使用昂贵和专业设备的临床环境中的受控环境。一种接近当前黄金标准方法的准确性的方法，双能 X 射线吸收测定法 (DXA)，同时只需要来自广泛可用的消费级设备的输入，将能够在野外测量这些重要的生物特征，从而实现数据收集以以前在时间和费用上令人望而却步的规模。我们描述了一种算法，用于从使用数字消费相机获取的单个正面二维图像预测三维 (3D) 身体形状和成分。