2018 年 84 巻 12 号 p. 996-1002
This paper presents a method to measure foot shape from a 3D point cloud as input captured from multiple directions using a smartphone depth camera. Such a 3D point cloud could potentially include noise or omit parts of the foot due to occlusion. To deal with this occlusion problem, we propose to use a dataset of 3D foot shapes collected by a precise 3D shape scanner of foot shapes. According to the dataset of 3D foot shapes, we can generate a deformable model by performing a principal component analysis (PCA) on the dataset. Then we minimize the error of the shape represented by the deformable model and the 3D point cloud acquired by the smartphone camera, to recover a complete 3D shape of the entire foot with high accuracy. We test this method by comparing the 3D shape produced by our proposed method to the 3D shape precisely measured by the 3D scanner. Our proposed method can scan the foot shape with an error of about 1.13mm.