# Mobile-AI-Based Docent System: Navigation and Localization for Visually Impaired Gallery Visitors
## 4 Research and Analysis
### Human Detection  
The relationship between facial measurements, height, and head height is significant, with the vertical face value changing proportionally to the individual's height [36]. Building on this insight, we proceeded to conduct tests to assess how the size of human heads varies with distance and height. This was done based on the principle that when an object is closer to the camera, it occupies a greater pixel count compared to when it is distant, enabling the measurement of the object's distance [37]. To conduct relevant tests, we collected data from a total of 5 individuals, each with heights of 153, 158, 170, 178, and 183 cm, respectively. Tests were conducted at three predetermined locations. At the first location, individuals stood at distances of 180 cm, 270 cm, and 360 cm away. They stood in an upright position while we adjusted the height of the smartphone hanging from the neck, measuring it at distances of approximately 100 cm and 150 cm above the ground level, respectively. While the positions of the individuals were fixed, their movements were not constrained. This decision was made to account for the fact that the smartphone, worn by individuals with visual impairments, would not be fixed in place, and thus, we aimed to conduct tests considering this movement. Initially, photos were taken at each location, and subsequently, using the system implemented on Android devices, the size of human heads was measured at each location where they were trained. The results of a test to determine the effect of human head size on height, conducted at a photographing distance of 180 cm and a photographing position of 150 cm above the ground, are depicted in Figure 9.  
As observed in Figure 9, while height does not have an absolute influence on facial size, it does appear to exert a certain degree of impact. Additionally, Figure 10 illustrates the effects on facial pixel size when the photographing position is varied at a distance of 180 cm. This test was conducted to understand how changes in the photographing position affect facial pixel size. The data labeled with \"_Low\" and \"_High\" in the legend were collected at ground heights of 100 cm and 150 cm, respectively. Although the movements  
Figure 9: The comparison of face sizes relative to height. were not constrained, resulting in variations in detection size, a similar trend to Figure 9 can be observed. Finally, we examined changes in face size by measurement location. In Figure 11, while there are overlapping pixel sections to some extent depending on the distance, it's noticeable that the sensitivity to distance is more pronounced compared to height and facial size. This result can be seen more clearly by looking at the average value in Table 3. Therefore, our system sets the face recognition pixel size to 2000 or more in order to recognize obstacles that may occur during route guidance, that is, people, and provide voice guidance to the visually impaired for obstacles recognized within a certain range. Figure 11: The relationship between measured distance and facial size. Figure 10: The relationship between height and facial size at different photographing heights. In high-density crowd scenarios where multiple individuals are detected, the system employs a proximity-based prioritization algorithm to focus on the nearest person. Due to the inverse relationship between perceived head size and distance in the visual field, the effective detection threshold is constrained to approximately 10 m. The system implements a comparative analysis of detected individuals and initiates an alert protocol based on the position of the nearest subject. The sequence diagram illustrated in Figure 12 delineates the system's operational framework. The image capture process commences simultaneously with the application initialization. Subsequently, the YOLO module conducts image analysis to determine the presence of multiple human subjects within the captured frame.