Foot measurement is necessary for personalized customization. Nowadays, people usually obtain their foot size by using a ruler or foot scanner. However, there are some disadvantages to this, namely, large measurement error and variance when using rulers, and high price and poor convenience when using a foot scanner. To tackle these problems, we obtain foot parameters by 3D foot reconstruction based on mobile phone photography. Firstly, foot images are taken by a mobile phone. Secondly, the SFM (Structure-from-Motion) algorithm is used to acquire the corresponding parameters and then to calculate the camera position to construct the sparse model. Thirdly, the PMVS (Patch-based Multi View System) is adopted to build a dense model. Finally, the Meshlab is used to process and measure the foot model. The result shows that the experimental error of the 3D foot reconstruction method is around 1 mm, which is tolerable for applications such as shoe tree customization. The experiment proves that the method can construct the 3D foot model efficiently and easily. This technology has broad application prospects in the fields of shoe size recommendation, high-end customized shoes and medical correction.
A New HRRP Reconstruction Method based on Joint Sparse Model
