# A Study on the Application of Walking Posture for Identifying Persons with Gait Recognition
###### Abstract
Hence, it is difficult to identify the human body's skeleton correctly. In recent years, significant progress has been made. For example, probabilistic image segmentation methods were used to outline objects in a picture that were clearly marked [13]. [PERSON] proposed a new method to solve joint detection and preprocess human body features. The method of estimating a person's posture [14] uses the relationships among the human body parts in space to encode movements, and the authors constructed a model architecture accordingly. [PERSON] et al. used deformation, appearance mixture type, and visual appearance score to build a depth model [15]. In 2015, [PERSON] et al. proposed evaluating the human body's posture in multiple frames [16]. The convolution architecture and a heatmap were used to make the effect better. [PERSON] et al. proposed stacking hourglasses for evaluating human posture, to understand the corresponding relationships between the human body and space. There is repeated use of top-down and bottom-up processes in the internal model, so that the performance of the network architecture improves. [PERSON] et al. proposed the concept of OpenPose [17]. OpenPose can grasp the joints of the human body and connect them to form a complete human skeleton, making it useful for obtaining information about the human body. A fast and accurate method will be conducive if it is used in body recognition. After much research, the posture of the human body, which was initially considered difficult, can be grasped more accurately. The accuracy of the posture of the human body is getting higher and higher, which also makes human behavior recognition have better accuracy. [PERSON] et al. proposed a method of using foot pressure for identity recognition [18], and used the properties of the rotation matrix to apply various angles. This research used foot width, height, foot pressure, and an embedded system to build a rapid user identification system. [PERSON] used gait recognition to distinguish the differences in each person's gait for identity recognition [19]. This study output each video frame into 18 feature points and used KNN for classification. [PERSON] et al. proposed using two-channel convolutional neural networks and support vector machines for gait recognition [20]. They proposed a new representation of gait features captured by the interval frame method and a convolutional neural network with two channels. In the existing identity recognition methods, particular image-based recognition targets require specific contexts. For example, it is challenging to perform identity recognition when face images are unavailable--e.g., when masks and sunglasses cover the face. In addition, the walking posture of each person, such as the frequencies and heights of hand and foot movements, may be habitual. Therefore, we aim to identify a person by his or her walking posture. We can also help determine a person's identity when he or she deliberately covers his or her face in certain behaviors, such as theft or other crimes. In our study, we found that different people do walk differently. Moreover, although there may be other small movements (grabbing the head, etc.) when walking, the overall frequencies and heights of hand and foot movements are consistent due to habit. Regarding people's emotions that may be involved in walking, we believe if there is variability in walking posture, it will be reflected in the positions of the 18 feature points (the head, arms, and legs). An individual's feature points usually change due to emotions when walking, which can be confirmed in most training sets. If we want to use information other than the face to identify a person's identity, the first thing that comes to mind is the way he or she moves. Everyone will be somewhat different when doing the same action. If we can find the differences between these movements, it will be of great benefit for automatic judgments, and when it comes to the movements that most people will naturally do, walking is key.