从常见二维图片中进行三维网格恢复以自动评估脊柱前凸症的身体姿势
Three-Dimensional Mesh Recovery from Common 2-Dimensional Pictures for Automated Assessment of Body Posture in Camptocormia.
作者信息
Wolke Robin, Gavriliuc Olga, Granert Oliver, Deuschl Günther, Margraf Nils G
机构信息
Department of Neurology Kiel University, Universitätskrankenhaus Schleswig-Holstein, Campus Kiel Kiel Germany.
Department of Neurology State University of Medicine and Pharmacy "Nicolae Testemitanu" Chisinau Moldova.
出版信息
Mov Disord Clin Pract. 2023 Jan 24;10(3):472-476. doi: 10.1002/mdc3.13647. eCollection 2023 Mar.
BACKGROUND
Three-dimensional (3D) human body estimation from common photographs is an evolving method in the field of computer vision. It has not yet been evaluated on postural disorders. We generated 3D models from 2-dimensional pictures of camptocormia patients to measure the bending angle of the trunk according to recommendations in the literature.
METHODS
We used the Part Attention Regressor algorithm to generate 3D models from photographs of camptocormia patients' posture and validated the resulting angles against the gold standard. A total of 2 virtual human models with camptocormia were generated to evaluate the performance depending on the camera angle.
RESULTS
The bending angle assessment using the 3D mesh correlated highly with the gold standard ( = 0.97, < 0.05) and is robust to deviations of the camera angle.
CONCLUSIONS
The generation of 3D models offers a new method for assessing postural disorders. It is automated and robust to nonperfect pictures, and the result offers a comprehensive analysis beyond the bending angle.
背景
从普通照片中进行三维（3D）人体估计是计算机视觉领域中一种不断发展的方法。该方法尚未在姿势障碍方面进行评估。我们根据文献中的建议，从弯腰驼背患者的二维图片生成3D模型，以测量躯干的弯曲角度。
方法
我们使用部分注意力回归算法从弯腰驼背患者姿势的照片生成3D模型，并将所得角度与金标准进行验证。总共生成了2个患有弯腰驼背的虚拟人体模型，以根据相机角度评估性能。
结果
使用3D网格进行的弯曲角度评估与金标准高度相关（= 0.97，<0.05），并且对相机角度的偏差具有鲁棒性。
结论
3D模型的生成提供了一种评估姿势障碍的新方法。它是自动化的，对不完美的图片具有鲁棒性，并且结果提供了超出弯曲角度的全面分析。
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