The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 13, 2024

Filed:

Jun. 29, 2020
Applicant:

Zhongyuan University of Technology, Henan, CN;

Inventors:

Xiaowei Song, Zhengzhou, CN;

Lei Yang, Zhengzhou, CN;

Menglong Li, Zhengzhou, CN;

Jianlei Xia, Zhengzhou, CN;

Shan Li, Zhengzhou, CN;

Yiping Chang, Zhengzhou, CN;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/62 (2017.01); G06T 7/80 (2017.01); G06T 7/73 (2017.01); G06T 7/593 (2017.01); H04N 13/246 (2018.01); H04N 13/239 (2018.01); G06V 20/54 (2022.01); G06V 10/44 (2022.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G06V 10/75 (2022.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G08G 1/017 (2006.01); G08G 1/056 (2006.01); G06F 18/213 (2023.01); H04N 23/60 (2023.01); G06T 7/285 (2017.01);
U.S. Cl.
CPC ...
G06T 7/285 (2017.01); G06F 18/213 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/593 (2017.01); G06T 7/62 (2017.01); G06T 7/75 (2017.01); G06T 7/85 (2017.01); G06V 10/449 (2022.01); G06V 10/757 (2022.01); G06V 10/82 (2022.01); G06V 20/41 (2022.01); G06V 20/54 (2022.01); G08G 1/0175 (2013.01); G08G 1/056 (2013.01); H04N 13/239 (2018.05); H04N 13/246 (2018.05); H04N 23/64 (2023.01); G06T 2207/10021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30241 (2013.01); G06T 2207/30244 (2013.01);
Abstract

The invention provides a method for intelligently measuring vehicle trajectory based on a binocular stereo vision system, including the following steps: inputting a dataset into an SSD (Single Shot Multibox Detector) neural network to train a license plate recognition model; calibrating the binocular stereo vision system, and recording videos of moving target vehicles; detecting the license plates in the video frames with the license plate recognition model; performing stereo matching on the license plates in the subsequent frames of the same camera and in the corresponding left-view and right-view video frames by a feature-based matching algorithm; reserving correct matching point pairs after filtering with a homography matrix; screening the reserved matching point pairs, and reserving the one closest to the license plate center as the position of the target vehicle in the current frame; performing stereo measurement on the screened and reserved matching point pairs to get the spatial position coordinates of the vehicle in the video frames; and generating the moving trajectory of the vehicle in time sequence. The present invention is easy to install and adjust, and can simultaneously measure multiple target vehicles in multiple directions and on multiple lanes.


Find Patent Forward Citations

Loading…