## 2 Methodology
### Posture Determination  
Because the perception of a hazardous object, such as equipment, by a worker depends on the worker's posture, a posture determination algorithm for determining posture was developed. The posture determination algorithm is based on human body joints obtained from pose estimation. During pose estimation, the human skeleton is acquired by connecting key points, such as the head, neck, shoulder, elbow, wrist, hip, knee, and ankle, which are human body parts. Worker posture is classified into \"upright posture\", \"stooped posture\", and \"dropped head\" state, and it is determined using a two-step discriminant based on the head, neck, and wrist coordinates. Discriminants for classifying a \"dropped head\" state and for classifying the \"stooped posture\" state when it is not in the \"dropped head\" state are shown in Figure 2.  
First, a discriminant is determined to distinguish the \"dropped head\" state. The \"dropped head\" state refers to when the worker is looking at the ground. In this case, the  
Figure 2: Flow chart of worker’s posture determination algorithm.  
head and neck coordinates are used, classified based on the vertical position of the head. The vertical position of the worker's head is calculated as follows:  
\[\Delta_{y}^{head}=\frac{P_{y}^{head}-P_{y}^{neck}}{H_{bbox}} \tag{1}\]  
where \(Pt\) is the coordinate value of the key points generated through pose estimation, \(H_{bbox}\) is the height of the bounding box, and \(\Delta_{y}^{head}\) is a constant that determines the position of the head. Pt is expressed as \(P_{Cordinate}^{leopoint}\) based on the body joint and the \(x\)- and \(y\)-coordinates of the image. \(P_{y}^{head}\) and \(P_{y}^{bek}\) are the \(y\) values of the head and neck, respectively, and \(\Delta_{y}^{head}\) consists of the difference between the two values. In addition, even with the same posture, it is normalized by \(H_{bbox}\) because the value is different for each perspective of the object. \(\Delta_{y}^{head}\) determines the vertical position of the worker's head and is classified into a \"dropped head\" state based on threshold value \(\delta_{1}\).  
Second, for workers not in the \"dropped head\" state, a discriminant is performed to distinguish the \"stooped head\" state. The \"stooped head\" state generally exists when a worker's waist is bent to perform groundwork. Therefore, regardless of the position of the worker's head, the \"stooped head\" state depends on the shape of the upper body. Hence, the neck and waist key points are used to distinguish them from the horizontal position of the upper body. The horizontal position of the worker's upper body is calculated using Equation (2):  
\[\Delta_{x}^{upper\ body}=\frac{P_{x}^{neck}-P_{x}^{n waist}}{H_{bbox}} \tag{2}\]  
where \(P_{x}^{neck}\) is the \(x\) value of the neck, \(P_{x}^{n waist}\) is the \(x\) value of the waist, and \(\Delta_{x}^{upper\ body}\) is a constant that determines the position of the upper body. The difference between the neck and waist, \(\Delta_{x}^{upper\ body}\), determines the horizontal position of the worker's upper body and is divided into a \"stooped posture\" state based on threshold \(\delta_{2}\). Because \(\delta_{1}\) and \(\delta_{2}\) are variables that depend on the position and angle where the image was captured, they are calculated using the heuristic determination of the actual CCTV (Section 4).