TY - GEN
T1 - Study on the Detection of Vehicles under Effect of Foreground Obstacles
AU - Wu, Yifan
AU - Yazawa, Syota
AU - Niizuma, Kiyozumi
AU - Kuroiwa, Takashi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Traffic accidents at intersections account for almost half of road shape classifications in Japan. If dangerous driving such as malicious tailgating will be predicted by tracking the vehicle in the intersection, it may be possible to prevent traffic accidents. Monitoring by CCTV may be solution of this problem, but it is not always easy to set up at desired location. 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 established by MLIT. Therefore, we have been reported on a method for detecting vehicles by fractal analysis of video taken from safe airspace beside the road. However, video recording at road side is affected by trees, traffic signs, utility poles and so on. In this study, we present a technique to reduce the influence of foreground obstacles such as roadside trees that prevent of the detection of vehicles.
AB - Traffic accidents at intersections account for almost half of road shape classifications in Japan. If dangerous driving such as malicious tailgating will be predicted by tracking the vehicle in the intersection, it may be possible to prevent traffic accidents. Monitoring by CCTV may be solution of this problem, but it is not always easy to set up at desired location. 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 established by MLIT. Therefore, we have been reported on a method for detecting vehicles by fractal analysis of video taken from safe airspace beside the road. However, video recording at road side is affected by trees, traffic signs, utility poles and so on. In this study, we present a technique to reduce the influence of foreground obstacles such as roadside trees that prevent of the detection of vehicles.
UR - http://www.scopus.com/inward/record.url?scp=85172031332&partnerID=8YFLogxK
U2 - 10.1109/PIERS59004.2023.10221268
DO - 10.1109/PIERS59004.2023.10221268
M3 - Conference contribution
AN - SCOPUS:85172031332
T3 - 2023 Photonics and Electromagnetics Research Symposium, PIERS 2023 - Proceedings
SP - 968
EP - 971
BT - 2023 Photonics and Electromagnetics Research Symposium, PIERS 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 Photonics and Electromagnetics Research Symposium, PIERS 2023
Y2 - 3 July 2023 through 6 July 2023
ER -
