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. 04, 2025

Filed:

Aug. 25, 2021
Applicant:

Honda Motor Co., Ltd., Tokyo, JP;

Inventors:

Jiachen Li, Albany, CA (US);

Haiming Gang, San Jose, CA (US);

Hengbo Ma, Albany, CA (US);

Chiho Choi, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2024.01); B60W 50/08 (2020.01); B60W 60/00 (2020.01); G01S 17/89 (2020.01); G01S 17/931 (2020.01); G06F 18/2433 (2023.01); G06F 18/25 (2023.01); G06V 10/44 (2022.01); G06V 10/46 (2022.01); G06V 10/80 (2022.01); G06V 20/58 (2022.01);
U.S. Cl.
CPC ...
G05D 1/0221 (2013.01); B60W 50/08 (2013.01); B60W 60/0027 (2020.02); G01S 17/89 (2013.01); G06F 18/2433 (2023.01); G06V 10/462 (2022.01); G06V 20/58 (2022.01); G01S 17/931 (2020.01); G06F 18/253 (2023.01); G06V 10/454 (2022.01); G06V 10/806 (2022.01);
Abstract

Object identification may be provided herein. A feature extractor may extract a first set of visual features, extract a second set of visual features, concatenate the first set of visual features, the second set of visual features, and a set of bounding box information, determine a number of object features and a global feature for a scene, and receive ego-vehicle feature information associated with an ego-vehicle. An object classifier may receive the number of object features, the global feature, and the ego-vehicle feature information, generate relational features with respect to relationships between each of the number of objects from the scene, and classify each of the number of objects from the scene based on the number of object features, the relational features, the global feature, the ego-vehicle feature information, and an intention of the ego-vehicle.


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