Proposing an Accurate Counting Method for Moving Objects by Optimizing Count-line Placement - HAGA, Yuzuki; SUZUKI, Yu; UNO, Haruka; TERABE, Shintaro; YAGINUMA, Hideki (Journal of the Eastern Asia Society for Transportation Studies, 2024)
In recent years, traffic measurements using general object detection AI have been used in various scenes. In Japan, there is a movement to always use CCTV cameras installed on major roads to constantly observe traffic. In general, the traffic volume measurement AI uses a cross-sectional traffic volume measurement using the line separation judgment algorithm, but the criteria and judgment basis for setting this Count-line is not clearly shown. In this study, a comparative verification is performed using a Kernel Density Estimation to set up an appropriate Count-line and manually setting. As a result, changing the position of the Count-line resulted in a maximum difference of 95.7% in measurement accuracy.