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:
Apr. 02, 2024

Filed:

Jun. 25, 2021
Applicant:

Chongqing University, Chongqing, CN;

Inventors:

Xichuan Zhou, Chongqing, CN;

Chunqiao Long, Chongqing, CN;

Yicong Peng, Chongqing, CN;

Assignee:

Chongqing University, Chongging, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06F 18/22 (2023.01); G06K 9/62 (2022.01); G06N 3/04 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06T 7/50 (2017.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
G06V 20/56 (2022.01); G06F 18/22 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06T 7/50 (2017.01); G06T 2207/10024 (2013.01);
Abstract

The invention relates to a real-time object detection and 3D localization method based on a single frame image. Comprising following steps: S1: inputting a 2D RGB image; S2: performing feature extraction on the 2D RGB image, extracting features of a deep network and a shallow network respectively; S3: carrying out 2D object detection and applying to subsequent modules; S4: estimating vertices, instance-level depth and center point of a 3D-box respectively; S5: adding a regularization term for maintaining horizontal locality into prediction of center point of a 3D-box to constrain and optimize the prediction of center point of the 3D-box; and S6: outputting a 2D RGB image with a 3D-box tag in combination with predictions of all modules. The invention increases the speed of model training convergence and the accuracy of 3D object detection and localization, and meets the accuracy requirements of an Advanced Driver Assistant System (ADAS) with a low hardware cost.


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