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:
Jun. 11, 2024

Filed:

May. 04, 2022
Applicant:

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

Inventors:

Jian Wan, Novi, MI (US);

Anthony Gerald King, Ann Arbor, MI (US);

Assignee:

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

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 19/00 (2011.01); B60K 35/00 (2006.01); G02B 27/01 (2006.01); G06T 7/70 (2017.01); B60K 35/23 (2024.01); B60K 35/28 (2024.01); B60K 35/65 (2024.01);
U.S. Cl.
CPC ...
G06T 19/006 (2013.01); B60K 35/00 (2013.01); G02B 27/0101 (2013.01); G06T 7/70 (2017.01); B60K 35/23 (2024.01); B60K 35/28 (2024.01); B60K 35/65 (2024.01); B60K 2360/166 (2024.01); B60K 2360/167 (2024.01); B60K 2360/177 (2024.01); B60K 2360/21 (2024.01); B60K 2360/25 (2024.01); G02B 2027/0138 (2013.01); G02B 2027/014 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30252 (2013.01);
Abstract

A set of training images are input into a neural network that outputs a pixel-wise phase matrix identifying pixels in the training images. Based on the pixel-wise phase matrix, a spatial light modulator (SLM) is actuated to output, onto a vehicle windshield, an augmented reality (AR) image including a plurality of sub-images each output in one of a plurality of focal planes. Each training image corresponds to one respective sub-image. A feedback image of the AR image is obtained via an image sensor. An offset is determined based on comparing the training images to the feedback image. Parameters of a loss function are updated based on the offset, and the updated parameters are provided to the neural network to obtain an updated offset.


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