US 12,008,722 B2
Multi-plane augmented reality image generation
Jian Wan, Novi, MI (US); and Anthony Gerald King, Ann Arbor, MI (US)
Assigned to Ford Global Technologies, LLC, Dearborn, MI (US)
Filed by Ford Global Technologies, LLC, Dearborn, MI (US)
Filed on May 4, 2022, as Appl. No. 17/736,158.
Prior Publication US 2023/0360331 A1, Nov. 9, 2023
Int. Cl. 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)
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)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
a spatial light modulator (SLM) arranged 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;
an image sensor positioned to obtain a feedback image of the AR image; and
a computer including a processor and a memory, the memory storing instructions executable by the processor programmed to:
input a set of training images into a neural network that outputs a pixel-wise phase matrix identifying pixels in the training images, wherein each training image corresponds to one respective sub-image;
actuate the SLM to output the AR image based on the pixel-wise phase matrix;
determine an offset based on comparing the training images to the feedback image; and
update parameters of a loss function based on the offset and provide the updated parameters to the neural network to obtain an updated offset.