## 4 Experiment
### The Experimental Results  
As can be seen from Table 1, the experimental error of foot length and foot width of the foot scanner is 0.70 mm and 0.48 mm, respectively. The experimental error of foot length and foot width of the 3D foot reconstruction method used in this paper is 1.09 mm and 1.07 mm, respectively. It can be seen that the experimental error of the 3D foot reconstruction method is still slightly larger than that of the foot scanner. However, the experimental error of the 3D foot reconstruction method is around 1 mm, which is tolerable for applications such as shoe tree customization. The method is also not limited by location and equipment, with high flexibility and convenience. In the process of preparing the foot data, we firstly used the camera of the smartphone to shoot around the foot at an angle of 45 degrees and 90 degrees from the magazine to obtain different height information and more than 60 photos were obtained. However, in the process of reconstruction by using Visual SFM, we found that only just over 20 photos were successfully matched in the feature detection and matching stage, which resulted in a poor result of the 3D foot model. We tried to increase the photos by reducing the distance when shooting, but the results did not improve. We guessed that the movement distance during manual shooting could not be controlled, resulting in a low correlation between photos. Therefore, we tried to use mobile phones to shoot video and cut the videos into photos through software. Finally, it was verified that the reconstruction effect of photos captured by video was better. The results obtained by the 3D reconstruction method based on the foot images were compared with the results obtained by the 3D foot-scanner, as shown in Figure 8. The model has a little geometric distortion in the heel, and the prominent features of the toes and soles are relatively complete; the expected requirements are met. Some vacancies appear on the medial side of the arch and the heel of the foot. The reason is that due to the height of the camera and the angle of shooting, there are some shooting corners that cause the above part to fail to reach enough point cloud data, which will affect the final modeling results. It can be improved by adjusting the shooting angle, replacing the sole reference, resetting the target position, and improving the dense reconstruction method. At the same time, the result can only show the shape and appearance of the foot's shape. It is necessary to calculate the length of the target object and other parameters by comparison with the reference object. There may be some experimental error in the process. These errors can also be reduced as much as possible by the error compensation method proposed by [PERSON] et al. [30]. Figure 8: 3D foot model comparison of foot-scanner and Multi-images. The advantage of the 3D foot reconstruction method based on mobile phone photography is that the operation is simple, convenient, low cost and easy to spread, and the user can complete the foot reconstruction work at home by using a mobile phone. We can use the mobile phone as the scene information acquisition device. The acquisition time is relatively short and free, which can quickly complete the information acquisition process for the target object. However, the acquisition time of laser scanning and other methods is relatively long, and it is generally determined by the surface area of the measured target and the sampling rate of the measured space, which results in the measurement of the 3D geometric structure unsuitable for the biological shape. The methods used in this paper also have some shortcomings. For example, the density of model sampling points obtained directly is limited by camera resolution and object characteristics, which cannot achieve the same sampling density as laser scanning or measurement methods based on structural fringe grating. Secondly, feature matching is an important problem to be solved.