## 5 Discussion  
Although the manual method is not perfect, it was chosen as a ground truth reference, due to no commercial system being available.  
The results provided by both methods varied for different types of landmarks. For the mid-surface projection, the highest average values of errors were noted for the lowest rib point (37.5 mm), croch \(\mathrm{C_{R}}\) (29.2 mm), and highest hip points \(\mathrm{H_{L}}\), \(\mathrm{H_{R}}\) (29.1 mm). All those points are related to lower parts of the torso, for which the shape was strongly affected by the weight of volunteers. The best performance  
Figure 17: Box chart of error distribution for orthogonal (**a**) and mid-surface projection (**b**).  
was achieved for neck back neck point N\({}_{\text{B}}\) (13.9 mm) and lowest chin point R\({}_{\text{L}}\), R\({}_{\text{R}}\) (15.1 mm), which were significantly less dependent on the body silhouette.  
Similar dependency on variation could have been observed for the orthogonal projection method, where the distribution of average distances and standard deviation showed that the best results were gained for chin lowest C\({}_{\text{L}}\) (16.1 mm) and wrist points W\({}_{\text{L}}\), W\({}_{\text{R}}\) (18.9 mm). The worst performance after filtering was noted for the elbow E\({}_{\text{L}}\), E\({}_{\text{R}}\) (32.7 mm) landmarks.  
Based on a comparison of the distribution of averages for different landmarks, an improvement for head- and limb-related ones could have been observed with the use of the mid-surface projection. It was caused by two factors. Firstly, in the case of the mid-surface approach, limbs were straightened during the unwrapping process, which led to reduction of the inclination impact and as a result decrease imperfect pose influence. Secondly, extrusion resulted in a reduced error per pixel. That effect can be observed on the neck back point (33% decrease of the distance in the case of the mid-surface projection).  
On the other hand, the orthogonal projection proved better performance for landmarks from the lower part of the torso. This was related to the convexity influence on the resolution of the projection. With rapid curvature changes, such as for the stomach area, rays of the mid-surface projection spread radially. The related points were more spatially separated than in the case of the orthogonal projection, which resulted in an overall lower resolution for this region. The possible solution of this problem would be the application of various resolutions by interpolation in the mid-surface projection in the region of the lower torso. This would lead to an increased density of rays and resolution. An alternative approach would be the utilization of a hybrid method consisting of the mid-surface and the orthogonal projections dependent on body part.  
Analysis of the process and results obtained showed the difference in standard deviation between both methods. In the case of the orthogonal projection, defects in the form of holes in the scan can occur when the wrong face of the model is visible. The N\({}_{\text{B}}\), A\({}_{\text{FF}}\) and C\({}_{\text{L}}\) landmarks were characterized by a significant increase of an error (up to 172.8 mm) for the incomplete data. This led to a strong decrease in the accuracy of the automatic marking process. Using the mid-surface method, such effects were minimized due to the projection from within the scan, where only one face was taken into consideration at once. In conclusion, a resistance to incomplete input data was improved. A comparison of images obtained via the mid-surface and the orthogonal back projections is presented in Figure 18. In the orthogonal approach, the unwanted front face of the scan can be seen and is mixed with the projected back view.  
Figure 18: Comparison of images generated via mid-surface (**a**) and orthogonal projection (**b**) for back view.