Facial expression recognition method based on facial motion unit combination features

Abstract

The invention discloses a facial expression recognition method based on facial motion unit combination features. The facial expression recognition method based on the facial motion unit combination features is used for solving the technical problem of low recognition rate of a single facial motion unit with an existing facial expression recognition method based on facial motion units. The technical scheme includes that the facial expression recognition method based on the facial motion unit combination features comprises the steps of building a large-scale facial expression data base, carrying out clustering of each category of facial expressions and corresponding training samples by using the affinity propagation (AP) clustering algorithm, judging arbitrary unit (AU) combinations in each sub-category, determining the number of the sub-categories under the same facial expression by combining main AU combinations, generating the number of the categories of the training sample by combining the sub-categories of all facial expressions, and carrying out classification training by using the support vector machine (SVM) method. According to the facial expression recognition method based on the facial motion unit combination features, the recognition rate of the single facial motion unit is improved, namely that average recognition rate of a single AU unit is improved from 87.5% in prior are to 90.1% and by 2.6%.

Description

technical field [0001] The invention relates to a facial expression recognition method, in particular to a facial expression recognition method based on facial action unit combination features. Background technique [0002] Facial expression recognition is an important research direction in the fields of human-computer interaction, machine learning, intelligent control and image processing, and has become a hot research topic at home and abroad. The expression recognition method based on facial activity units is based on the facial activity coding system in psychology, and the expression recognition is performed by establishing the relationship between the visual features of the face and the facial activity units, as well as the relationship between the facial activity units and the six basic expressions. The introduction of facial activity units reduces the gap between the complex visual features of human faces and the six basic expressions. [0003] Document 1 "Velusamy S...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the existing facial expression recognition method based on facial action units to the poor recognition rate of a single facial action unit, the present invention provides a facial expression recognition method based on the combined features of facial action units

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