LEARNING METHOD AND APPARATUS FOR FACIAL EXPRESSION RECOGNITION FACIAL EXPRESSION RECOGNITION METHOD USING ELECTROMYOGRAM DATA

摘要

Disclosed is a learning method and apparatus for increasing a recognition success rate of facial expression recognition using EMG data. The disclosed learning method for facial expression recognition includes: extracting a first feature value from EMG data of a user's face portion for a plurality of facial expressions; And learning a facial expression class for the EMG data by using the first feature value and a second feature value obtained from reference EMG data for the facial expression, wherein the facial expression class for the EMG data The learning step includes: calculating a first average value and a first covariance value of the first feature value for the facial expression class; Generating a first parameter by weighting averaging a second average value and the first average value of the second feature value for the facial expression class; And generating a second parameter by a weighted average of the second covariance value and the first covariance value of the second feature value for the facial expression class, wherein the first and second parameters are LDA models. This parameter is for.