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:
Aug. 11, 2020

Filed:

Jan. 15, 2018
Applicant:

Beihang University, Beijing, CN;

Inventors:

Xiaowu Chen, Beijing, CN;

Jia Li, Beijing, CN;

Yafei Song, Beijing, CN;

Yifan Zhao, Beijing, CN;

Qinping Zhao, Beijing, CN;

Assignee:

BEIHANG UNIVERSITY, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06T 7/10 (2017.01); G06N 3/08 (2006.01); G06K 9/00 (2006.01); G06T 7/11 (2017.01);
U.S. Cl.
CPC ...
G06T 7/10 (2017.01); G06K 9/00 (2013.01); G06K 9/00208 (2013.01); G06K 9/00664 (2013.01); G06K 9/6274 (2013.01); G06N 3/08 (2013.01); G06T 7/11 (2017.01); G06T 2200/04 (2013.01); G06T 2200/08 (2013.01); G06T 2207/20081 (2013.01);
Abstract

Embodiments of the present invention provide a method and a device for three-dimensional feature-embedded image object component-level semantic segmentation, the method includes: acquiring three-dimensional feature information of a target two-dimensional image; performing a component-level semantic segmentation on the target two-dimensional image according to the three-dimensional feature information of the target two-dimensional image and two-dimensional feature information of the target two-dimensional image. In the technical solution of the present application, not only the two-dimensional feature information of the image but also the three-dimensional feature information of the image are taken into consideration when performing the component-level semantic segmentation on the image, thereby improving the accuracy of the image component-level semantic segmentation.


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