@techreport{oai:ipsj.ixsq.nii.ac.jp:00220154,
 author = {呉, ー帆 and 矢澤, 翔大 and 新妻, 清純 and 黒岩, 孝 and Yifan, Wu and Syota, Yazawa and Kiyozumi, Niizuma and Takashi, Kuroiwa},
 issue = {5},
 month = {Sep},
 note = {Accidents nearby intersections account for almost half on road shape classifications. If dangerous driving such as malicious tailgating will be predicted by tracking the vehicle nearby the intersection, it may be possible to prevent traffic accidents. It seems to be easy for drone to detect vehicles relatively at the right above intersection, but flight over the road is prohibited by the aviation law. Therefore, we have studied on a method for detecting vehicles by fractal analysis of drone video taken from safe airspace beside the road. In this study, we will present a technique to reduce the influence of foreground obstacles such as roadside trees that prevent of our method., Accidents nearby intersections account for almost half on road shape classifications. If dangerous driving such as malicious tailgating will be predicted by tracking the vehicle nearby the intersection, it may be possible to prevent traffic accidents. It seems to be easy for drone to detect vehicles relatively at the right above intersection, but flight over the road is prohibited by the aviation law. Therefore, we have studied on a method for detecting vehicles by fractal analysis of drone video taken from safe airspace beside the road. In this study, we will present a technique to reduce the influence of foreground obstacles such as roadside trees that prevent of our method.},
 title = {前景の障害物を考慮した二車線道路における走行車両の追跡に関する研究},
 year = {2022}
}