US 12,425,556 B2
Learning-based light field compression for tensor display
Zhu Li, Overland Park, KS (US)
Assigned to Adeia Guides Inc., San Jose, CA (US)
Filed by Adeia Guides Inc., San Jose, CA (US)
Filed on Apr. 25, 2022, as Appl. No. 17/727,970.
Prior Publication US 2023/0344974 A1, Oct. 26, 2023
Int. Cl. H04N 13/122 (2018.01); H04N 13/161 (2018.01); H04N 13/388 (2018.01)
CPC H04N 13/122 (2018.05) [H04N 13/161 (2018.05); H04N 13/388 (2018.05)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
training a machine learning model to:
accept as input synthetic aperture image (SAI) training data for a three-dimensional (3D) display, the 3D display comprising a plurality of layers; and
output respective pixel representations of the SAI training data for each of the plurality of layers of the 3D display;
inputting image data to the trained machine learning model;
determining, using the trained machine learning model, respective pixel representations of the input image data for each of the plurality of layers of the 3D display;
encoding, at one or more servers, the respective pixel representations of the input image data, wherein the encoding comprises compressing the respective pixel representations of the input image data; and
transmitting, by the one or more servers to the 3D display over a communications network, the encoded respective pixel representations of the input image data, wherein the 3D display decodes the encoded respective pixel representations of the input image data and displays content based on the decoding.