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:
Mar. 12, 2024

Filed:

Feb. 09, 2021
Applicants:

Ford Global Technologies, Llc, Dearborn, MI (US);

Board of Trustees of Michigan State University, East Lansing, MI (US);

Inventors:

Robert Parenti, Dearborn, MI (US);

Adil Siddiqui, Farmington Hills, MI (US);

Mahmoud Yousef Ghannam, Canton, MI (US);

Yasodekshna Boddeti, East Lansing, MI (US);

Assignees:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H04N 7/18 (2006.01); B60H 1/00 (2006.01); B60R 21/015 (2006.01); G06F 18/22 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06T 7/73 (2017.01); G06V 10/147 (2022.01); G06V 20/59 (2022.01); G06V 40/10 (2022.01); G06V 40/20 (2022.01); H04N 13/204 (2018.01); H04N 23/90 (2023.01);
U.S. Cl.
CPC ...
H04N 7/188 (2013.01); B60H 1/00742 (2013.01); B60H 1/00871 (2013.01); B60R 21/01538 (2014.10); B60R 21/01542 (2014.10); G06F 18/22 (2023.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06T 7/73 (2017.01); G06V 10/147 (2022.01); G06V 20/59 (2022.01); G06V 40/10 (2022.01); G06V 40/20 (2022.01); H04N 13/204 (2018.05); H04N 23/90 (2023.01); G06T 2207/20081 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30268 (2013.01);
Abstract

A two-dimensional image of a vehicle occupant in a vehicle is collected. The collected two-dimensional image is input to a machine learning program trained to output one or more reference points of the vehicle occupant, each reference point being a landmark of the vehicle occupant. One or more reference points of the vehicle occupant in the two-dimensional image is output from the machine learning program. A location of the vehicle occupant in an interior of the vehicle is determined based on the one or more reference points. A vehicle component is actuated based on the determined location. For each of the one or more reference points, a similarity measure is determined between the reference point and a three-dimensional reference point, the similarity measure based on a distance between the reference point and the three-dimensional reference point.


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