US 12,327,430 B2
Simulated capacitance measurements for facial expression recognition training
Jouya Jadidian, Los Gatos, CA (US); Calin Cristian, Iasi (RO); and Petre-Alexandru Arion, Timisoara (RO)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Jun. 28, 2022, as Appl. No. 17/809,438.
Claims priority of application No. 2022-00361 (RO), filed on Jun. 24, 2022.
Prior Publication US 2023/0419722 A1, Dec. 28, 2023
Int. Cl. G06V 40/16 (2022.01); G01S 13/89 (2006.01); G06N 3/08 (2023.01); G06V 10/82 (2022.01)
CPC G06V 40/174 (2022.01) [G01S 13/89 (2013.01); G06N 3/08 (2013.01); G06V 10/82 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method for training a neural network for facial expression recognition, the method comprising:
recognizing a plurality of digital human face models; and
for each of the plurality of digital human face models:
simulating a plurality of simulated facial expressions;
for each of the plurality of simulated facial expressions, finding simulated capacitance measurements for an array of simulated radio frequency (RF) antennas; and
providing the simulated capacitance measurements for each simulated facial expression as input training data to a neural network configured to output facial expression parameters based on input capacitance measurements.