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:
Oct. 17, 2023

Filed:

Jul. 19, 2022
Applicant:

Plusai, Inc., Cupertino, CA (US);

Inventors:

Hao Zheng, Saratoga, CA (US);

David Wanqian Liu, Los Altos, CA (US);

Timothy Patrick Daly, Jr., San Jose, CA (US);

Assignee:

PlusAI, Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/02 (2020.01); G06T 7/593 (2017.01); G05D 1/00 (2006.01); G06T 7/521 (2017.01); G06V 20/58 (2022.01); G06V 20/64 (2022.01); G06F 18/25 (2023.01); G06V 10/774 (2022.01); G06V 10/80 (2022.01);
U.S. Cl.
CPC ...
G06T 7/593 (2017.01); G05D 1/0088 (2013.01); G05D 1/0236 (2013.01); G05D 1/0257 (2013.01); G05D 1/0293 (2013.01); G06F 18/251 (2023.01); G06T 7/521 (2017.01); G06V 10/774 (2022.01); G06V 10/803 (2022.01); G06V 20/58 (2022.01); G06V 20/64 (2022.01); G06T 2207/10021 (2013.01); G06T 2207/20004 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/30252 (2013.01);
Abstract

The present teaching relates to a method, system, medium, and implementation of processing image data in an autonomous driving vehicle. Sensor data acquired by one or more types of sensors deployed on the vehicle are continuously received. The sensor data provide different information about surrounding of the vehicle. Based on a first data set acquired by a first sensor of a first type of the one or more types of sensors at a specific time, an object is detected, where the first data set provides a first type of information about the surrounding of the vehicle. Depth information of the object is then estimated via object centric stereo at object level based on the object detected as well as a second data set acquired by a second sensor of the first type of the one or more types of sensors at the specific time. The second data set provides the first type of information about the surrounding of the vehicle with a different perspective as compared with the first data set.


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