# Human Height Estimation by Color Deep Learning and Depth 3D Conversion
## 4 Experiment Results
The estimated error in walking toward the camera is larger than the others. The reason is that the vertical length of the human body is reduced because human knees are bent to a certain degree while walking. Figure 15 shows the positions of \(d_{h}\) and \((x_{f},y_{f})\) before and after the correction of the head-top and the foot-bottom, respectively. The green and red points in Figure 15 represent the head-top and  
Figure 14: Results of height estimation in standing and walking states. Figure 12: Results of height estimation depending on methods of human body region extraction. Figure 13: Results of height estimation according to distance between camera and human body. foot-bottom points, respectively. In Figure 15a, the position of \(d_{h}\) is on the hair area, so \(d_{h}\) has some error and the changes in \(d_{h}\) are large as shown in Figure 16. After correcting \(d_{h}\), the changes is smaller. The changes of the estimated human body height are reduced after correcting of the foot-bottom point as shown in Figure 17. Two persons whose actual heights are 182 cm and 165 cm are estimated as 188.6 cm and 181.5 cm before correcting \(d_{h}\), respectively, as 172.2 cm and 163.3 cm after the correction of the head-top point, respectively and as 181.5 cm and 163.1 cm after the correction of both head-top and foot-bottom points, respectively. Figure 18 shows the results of the human-height estimation depending on \(r_{0}\) and \(T_{o}\), which are the parameters for (8) and (9) when \(d_{0}\) is 2000. The estimated height drops sharply when \(r_{0}\) is less than or equal to 2 and decreases smoothly when \(r_{0}\) is larger than 2. In addition, the estimated height linearly increases when \(T_{o}\) is less than or equal to 250 and slowly increases when \(T_{o}\) is larger than 250. Body height is estimated most accurately when \(r_{0}\) is 2 and \(T_{o}\) is 125. Figure 16: Changes in \(d_{h}\) according to frame order. Figure 17: Result of height estimation after correction of \(d_{h}\) and \((x_{f},y_{f})\). Figure 11:0 Positions of \(d_{h}\) and \((x_{f},y_{f})\). (**a**) Before correction; (**b**) after correction. Tables 2-4 show the results of the human-height estimation depending on human body postures for 10 persons. All of persons are captured within a range of 2.5 m to 4 m from the camera. Each person is captured with 150 frames. The error of the human-height estimation is calculated as follows:  
Figure 11:1  
where \(\overline{H}\) and \(H_{actual}\) are the average of the corrected human heights by (12) and an actual height for a person, respectively. When the human body region is extracted by mask R-CNN, the errors of the human-height estimation with standing, lateral walking and walking towards the camera are 0.7%, 1.3% and 1.8%, respectively. The accurate foot-bottom for the human-height estimation is the point of a foot heel which is on the ground. However, the bottommost pixel of the body region which is extracted as the foot-bottom point is usually a foot toe point in the proposed method. The position difference between the foot heel and foot toe points may make the error of the human-height estimation. The human-height estimation errors with standing, lateral walking, and walking towards the camera are 2.2%, 2.9%, 4.6%, respectively, when the body region is extracted by the background depth image. The human-height estimation using only depth frames has more error than using both color and depth frames.