# Area of Interest Tracking Techniques for Driving Scenarios Focusing on Visual Distraction Detection
## 2 Methods
### Processing of Measurement
#### 2.3.2 Gaze on Road  
In our research, we have formulated a method to guarantee effective assessment of driver attention. This involves strategically positioning four ID tags on the windshield, which serve to delineate the driver's road view field as an AOI. These tags are positioned to form a boundary that frames the driver's view of the road. When the driver's gaze is located within the confines of this boundary, it is indicative of the driver's focus on the road. To ascertain the direction of the gaze, we analyze whether it falls to the left of the boundary lines, which are delineated by connecting these tags in a counterclockwise sequence. It is important to note that these ID tags are not situated precisely at the corners of the windshield. Therefore, we have implemented specific adjustments to their placement, which are elaborately described in Figure 5. This adjustment is critical to ensure the accurate determination of whether the driver's gaze is directed towards the road.  
In our experimental setup, we utilize marking points placed at the four corners of the windshield to define the specific AOI. When the driver's gaze is located within this demarcated area, it is interpreted as focusing on the road ahead, and the visualization shows green color indicators. Additionally, a central green mark is used to signify the actual position of the driver's gaze. The larger diameter green circle with a yellow frame represents the precise and fixation state of gaze identified using the 'Pupil Labs Software', shown in the raw videos that aid visualization, independent of our own analysis.  
A key aspect of our methodology is the implementation of an interpolation procedure between successive video frames. This procedure allows us to accurately track the position of these points, even in instances where the associated ID tag is not directly detected in a particular frame. It is important to note, however, that this interpolation technique is most effective when the absence of the tag from the frame is for relatively brief durations. Moreover, our approach accounts for scenarios where the known position of the ID tag may not be within the FOV. In such cases, the previously mentioned points can still be accurately determined based on their known positions relative to the ID tags. A practical demonstration of this scenario is shown in Figure 6, where the effectiveness of the method in tracking gaze position regardless of the direct visibility of ID tags is shown, and the red color of the corner points indicates the gaze-off-road condition. This aspect underscores the robustness of our system in maintaining accurate gaze tracking under various conditions.  
Figure 5: Gaze position (yellow circle with green fill), detected tags (blue squares), compensated tag positions (dots in the corners) and “gaze-on-road” indication (dots are green not red).  
In our study, as an alternative analytical approach, we consider any gaze that does not fall within the specified boundary (gaze-off-road case) as an \"Eyes-Off-The-Road\" scenario. This demarcation is essential to identify instances where the driver is not looking at the road, which is a critical factor in monitoring visual distraction when conducting a specific CDS. In cases where the experiment requires the subject to perform complex activities, consideration should be given to modifying the boundaries of the usable FOV (e.g., by adding mirrors) to make the measurement more accurate. Further investigation in this regard involves the measurement of TEORT, which provides a quantitative assessment of the duration for which the driver's attention is diverted away from the road, thereby offering valuable insights for visual distraction monitoring in driving scenarios.