Three‐Dimensional Mesh Recovery from Common 2‐Dimensional Pictures for Automated Assessment of Body Posture in Camptocormia

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 (R = 0.97, P < 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.