Title:
進行方向判定装置
Document Type and Number:
Japanese Patent JP7247268
Kind Code:
B2
Abstract:
To provide a traveling direction determination device that does not erroneously determine a traveling direction.SOLUTION: A traveling direction determination device comprises: a vehicle tracking function in which an arithmetic processing unit tracks a vehicle V moving in a bird's-eye view image F as a frame portion W with respect to a traffic road of an intersection K of the bird's-eye view image F input from an imaging unit; and a determination function for determining a traveling direction of the vehicle V by that an inflow line Li is set on an upstream side where the vehicle V in the bird's-eye view image F flows into the intersection K, an outflow line Lo is respectively set on a downstream side of traveling directions of a straight, a right turn, and a left turn where the vehicle V flows out from the intersection K, a center point of the frame portion W is set as a determination point H, and after the determination point H passes the inflow line Li, the outflow line Lo through which the vehicle first passes is detected.SELECTED DRAWING: Figure 4
Inventors:
Atsushi Oketani
Application Number:
JP2021103413A
Publication Date:
March 28, 2023
Filing Date:
June 22, 2021
Export Citation:
Assignee:
Kyosan Manufacturing Co., Ltd.
International Classes:
G08G1/056; G06T7/00; G06T7/70; G08G1/04; H04N7/18
Domestic Patent References:
| JP2019207651A | ||||
| JP2009258919A |
Other References:
写真計測ソフト『SingleViewビデオトラッカー』適用事例(動体解析を交通量調査、交通状況調査に利用),日本,株式会社アイティーティー,2018年09月25日,https://www.ittc.co.jp/blog/2018/08/08/singleview_case5/
Takayuki Iida,AIで通行量調査の映像解析精度を上げるのに苦労した,日本,2020年03月07日,https://web.archive.org/web/20200307151435/https://qiita.com/ComputerVision/items/fc64317006c25f37cc3e
古賀,[実例紹介]AI技術を活用した無人での交差点における自動車交通量の測定,日本,株式会社Present Square,2021年01月12日,https://deepsquare.jp/2021/01/traffic-count-crossroads/
Kristian Kovacic, Edouard Ivanjko, Hrvoje Gold,Real time vehicle detection and tracking on multiple lanes,Poster Proceedings, WSCG 2014 Conference on Computer Graphics, Visualization and Computer Vision,2014年,67-72,https://core.ac.uk/download/pdf/295560258.pdf
Erhan Bas, A. Murat Tekalp, F. Sibel Salman,Automatic Vehicle Counting from Video for Traffic Flow Analysis,IEEE,2007年07月,http://www.researchgate.net/publication/4268914_Automatic_Vehicle_Counting_from_Video_for_Traffic_ Flow_Analysis
古賀,【実例紹介】AI技術を活用した無人での交差点における自動車交通量の測定,日本,株式会社Present Square,2021年01月12日,https://deepsquare.jp/2021/01/traffic-count-crossroads/
Takayuki Iida,AIで通行量調査の映像解析精度を上げるのに苦労した,日本,2020年03月07日,https://web.archive.org/web/20200307151435/https://qiita.com/ComputerVision/items/fc64317006c25f37cc3e
古賀,[実例紹介]AI技術を活用した無人での交差点における自動車交通量の測定,日本,株式会社Present Square,2021年01月12日,https://deepsquare.jp/2021/01/traffic-count-crossroads/
Kristian Kovacic, Edouard Ivanjko, Hrvoje Gold,Real time vehicle detection and tracking on multiple lanes,Poster Proceedings, WSCG 2014 Conference on Computer Graphics, Visualization and Computer Vision,2014年,67-72,https://core.ac.uk/download/pdf/295560258.pdf
Erhan Bas, A. Murat Tekalp, F. Sibel Salman,Automatic Vehicle Counting from Video for Traffic Flow Analysis,IEEE,2007年07月,http://www.researchgate.net/publication/4268914_Automatic_Vehicle_Counting_from_Video_for_Traffic_ Flow_Analysis
古賀,【実例紹介】AI技術を活用した無人での交差点における自動車交通量の測定,日本,株式会社Present Square,2021年01月12日,https://deepsquare.jp/2021/01/traffic-count-crossroads/
Attorney, Agent or Firm:
Yohei Hibiya
Hibiya Masahiko
Hibiya Masahiko