Proposing an Accurate Counting Method for Moving Objects by Optimizing Count-line Placement

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 volu...

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Bibliographic Details
Published inJournal of the Eastern Asia Society for Transportation Studies Vol. 15; pp. 387 - 397
Main Authors HAGA, Yuzuki, YAGINUMA, Hideki, TERABE, Shintaro, UNO, Haruka, SUZUKI, Yu
Format Journal Article
LanguageEnglish
Published Eastern Asia Society for Transportation Studies 2024
Subjects
multi-object tracking
object detection
traffic volume measurement
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Summary: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.
ISSN:1881-1124
DOI:10.11175/easts.15.387