# A Study on the Application of Walking Posture for Identifying Persons with Gait Recognition
## 2 Material and Methods  
The procedure of this experiment can be divided into seven parts (Figure 1). (1) Use the GoPro Hero5 camera to collect the training data. (2) After collecting the data, clean the data and cut out the unnecessary parts (such as turning around and no-person images) to facilitate the subsequent experiments. (3) After removing the unnecessary parts, use OpenPose to detect the skeleton, obtain the human body's feature points (Figure 2), and use these data for training. (4) The default is 30 fps, meaning 30 frames are selected as a data set. (5) Since the starting positions of the selected data are different, we need to normalize the action so that the starting positions of each group are from the same place. (6) The model must be trained after the final data preprocessing. We implemented LSTM on the Tensorflow platform for training and testing. (7) Use the model to perform final identification. * Hardware and equipment  
The equipment used in this experiment was a GoPro Hero5, which has 4K resolution and a built-in linear correction function. Therefore, the images obtained will not be distorted. First, we used the GoPro Hero5 camera to create a training video of the subject. As shown in Figure 3, we set up the tripod vertically at a distance of 3.5 m from the subject. After setting up the camera, we asked the subject to walk from the far right side of the camera screen to the left side. After walking to the left side, we continued to walk forward until the subject disappeared from the screen. Figure 1: Architecture flowchart. Figure 2: Twenty-five feature points were detected by OpenPose [17]. The points represent as follows: 0 is the nose; 1 is the neck; 2 is the right shoulder; 3 is the right elbow; 4 is the right wrist; 5 is the left shoulder; 6 is the left elbow; 7 is the left wrist; 8 is the middle hip; 9 is the right hip; 10 is the right knee; 11 is the right ankle, 12 is the left hip; 13 is the left knee; 14 is the left ankle; 15 is the right eye; 16 is the left eye; 17 is the right ear; 18 is the left ear; 19 is the left big toe; 20 is the left small toe; 21 is the left heel; 22 is the right big toe; 23 is the right small toe; 24 is the right heel. Furthermore, after the character disappeared, we asked the subject to turn 180 degrees and walk back. Next, the subject reappeared in the field of view and then walked to the far right side of the camera until the subject disappears from the screen. Finally, after about 10 min of video capture, the subject was asked to perform the same action again. This step was completed after five subjects were filmed. The resolution of the recorded video was 1920 \(\times\) 1080 and 60 fps. * Video cleaning After the image was taken, we had to preprocess (video cleaning) the filmed video to ensure the final data were correct. First, because the film is a repeated video of the same behavior of walking to the left and walking to the right, and because there was a short period when the person disappeared during the two behaviors, the film had to be cut into several segments of varying length. The rules for these cuts were to divide the rightmost walk into the first category and the leftmost walk into the second category, and finally, to cut out the video of the time when the character disappears. After completing the above actions, two categories of different video lengths were obtained. Thus, twenty categories of films were obtained after the experiment with ten people. Since the turning part may be filmed during filming, we also cut out the turning part. In addition, the part that disappeared from the picture had to be cut out. Figure 4 shows that after the video was cleaned, everyone was divided into two categories: one with walking to the left and the other with walking to the right. * Skeleton Detection After that, we wanted to use the differences in each person's walking style to make a judgment because we needed to perform body recognition, and OpenPose can extract the key points of the human body.