# Occlusion-Aware Worker Detection in Masonry Work: Performance Evaluation of YOLOv8 and SAMURAI
## 2 Methodology
### Experiment Design and Data Collection  
This section describes the experimental design and data collection process to evaluate the performance of YOLOv8 and SAMURAI in brick transportation and brick laying tasks. The experiment was conducted in an outdoor environment simulating a construction site. Figure 2a illustrates the experimental setup, showing the fixed camera position and the relative locations of the worker and bricks. A single fixed camera was used to capture two tasks performed by the worker: (1) brick transportation and (2) brick laying. The camera was positioned to clearly capture the worker from the front.  
Figure 1: Research framework.  
Figure 2: Collected data: (**a**) experiment site; (**b**) carrying bricks in the non-occlusion state; (**c**) carrying bricks in the partial occlusion state; (**d**) carrying bricks in the severe occlusion state; (**e**) brick laying in the non-occlusion state; (**f**) brick laying in the partial occlusion state; and (**g**) brick laying in the severe occlusion state.  
In the brick transportation task, the worker pushed a trolley loaded with bricks, and the level of occlusion was classified based on the degree to which the worker's body was obstructed by an obstacle. Figure 1(b)-d visually represent these occlusion levels: Case 1 (non-occlusion) occurred when the worker's entire body was visible without any obstruction; Case 2 (partial occlusion) occurred when the obstacle obscured the worker below the knees; and Case 3 (severe occlusion) occurred when the obstacle obscured the worker from the waist up, significantly limiting visibility. The intersection over union (IoU) values for each occlusion level in the brick transportation task were as follows: Case 1 (non-occlusion) ranged between 0.85 and 0.92, with an average IoU of 0.89; Case 2 (partial occlusion) ranged between 0.67 and 0.75, with an average IoU of 0.71; and Case 3 (severe occlusion) exhibited the lowest values, ranging from 0.45 to 0.58, with an average IoU of 0.52.  
In the brick laying task, the worker crouched while stacking bricks, adding one layer at a time until reaching a total of 13 layers. The levels of occlusion were classified based on the degree to which the worker's body was obscured by the stacked bricks. As depicted in Figure 1(e)-g, Case 1 (non-occlusion) occurred when the worker's feet were visible (up to two-three layers of bricks); Case 2 (partial occlusion) occurred when only the worker's upper body was visible (up to seven-eight layers); and Case 3 (severe occlusion) occurred when only the worker's face was visible (up to twelve layers). For the brick laying task, IoU values varied depending on the occlusion level: Case 1 (non-occlusion) had IoU values between 0.82 and 0.90, with an average of 0.86; Case 2 (partial occlusion) had values between 0.55 and 0.68, averaging 0.61; and Case 3 (severe occlusion) demonstrated the lowest IoU values, ranging from 0.38 to 0.50, with an average of 0.44.  
For each task, videos were recorded until the worker reached each occlusion level. The collected video frames were annotated with bounding boxes around the worker, and the resulting dataset was used to evaluate the performance of YOLOv8 and SAMURAI, as described in the subsequent sections.