Simulated capacitance measurements for facial expression recognition training
AssigneeMicrosoft Technology Licensing, LLC
InventorsJouya JADIDIAN, Calin CRISTIAN, Petre-Alexandru ARION
Life of this patent
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Abstract
A method for training a neural network for facial expression recognition includes recognizing a plurality of digital human face models. For each of the plurality of digital human face models, a plurality of simulated facial expressions are simulated. Simulated capacitance measurements for an array of simulated radio frequency (RF) antennas are found for each of the plurality of simulated facial expressions. The simulated capacitance measurements for each simulated facial expression are provided as input training data to a neural network configured to output facial expression parameters based on input capacitance measurements.
Claims20
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.
A computing system, comprising:
- a communications subsystem;
- a logic subsystem;
- and
- a storage subsystem holding instructions executable by the logic subsystem to:
- receive, from a plurality of compute nodes via the communications subsystem, simulated capacitance measurements based on a simulated spatial arrangement of an array of simulated radio frequency (RF) antennas relative to a digital human face model with a simulated facial expression;
- and
- provide the simulated capacitance measurements to a neural network configured to output facial expression parameters based on input capacitance measurements.
A method for training a neural network for facial expression modeling, 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 based on a simulated spatial arrangement of the array of simulated RF antennas relative to the digital human face model with the simulated facial expression;
- 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, the input training data labeled with simulated facial expression parameters for the simulated facial expression;
- and
- training the neural network to reduce an error between the output facial expression parameters and the simulated facial expression parameters labeling the input training data.
Dependencies are inferred from the claim text.