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:
Dec. 20, 2022

Filed:

Apr. 29, 2022
Applicant:

Tsinghua University, Beijing, CN;

Inventors:

Xinyu Zhang, Beijing, CN;

Li Wang, Beijing, CN;

Jun Li, Beijing, CN;

Lijun Zhao, Beijing, CN;

Zhiwei Li, Beijing, CN;

Shiyan Zhang, Beijing, CN;

Lei Yang, Beijing, CN;

Xingang Wu, Beijing, CN;

Hanwen Gao, Beijing, CN;

Lei Zhu, Beijing, CN;

Tianlei Zhang, Beijing, CN;

Assignee:

TSINGHUA UNIVERSITY, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06V 10/80 (2022.01); G06V 10/40 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06N 3/04 (2006.01); G06T 7/73 (2017.01);
U.S. Cl.
CPC ...
G06V 10/806 (2022.01); G06N 3/0454 (2013.01); G06T 7/73 (2017.01); G06V 10/40 (2022.01); G06V 10/82 (2022.01); G06V 20/588 (2022.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

A vision-LiDAR fusion method and system based on deep canonical correlation analysis are provided. The method comprises: collecting RGB images and point cloud data of a road surface synchronously; extracting features of the RGB images to obtain RGB features; performing coordinate system conversion and rasterization on the point cloud data in turn, and then extracting features to obtain point cloud features; inputting point cloud features and RGB features into a pre-established and well-trained fusion model at the same time, to output feature-enhanced fused point cloud features, wherein the fusion model fuses RGB features to point cloud features by using correlation analysis and in combination with a deep neural network; and inputting the fused point cloud features into a pre-established object detection network to achieve object detection. A similarity calculation matrix is utilized to fuse two different modal features.


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