Facial expression identification method

Abstract

The invention discloses a facial expression identification method and relates to a method for identifying images. The facial expression identification method is a facial expression identification method which extracts expression textural characteristics using a center symmetrical ternary patterns (CSTP) algorithm. The method comprises steps of preprocessing a facial expression image; extracting facial expression textural characteristics on each sub-block of the facial expression image; and determining final facial expression textural characteristics of the facial expression image. Therefore, the facial expression identification is completed. The method overcomes problems that texture description is not fine due to a complex identification background and the identification rate is not high in the prior art.

Description

technical field [0001] The technical solution of the present invention relates to a method for recognizing graphics, in particular to a method for recognizing human facial expressions. Background technique [0002] Facial expression recognition is a challenging research topic in the field of computer vision, and it is of great significance in psychology and human-computer interaction research. In recent years, facial expression recognition technology has developed rapidly. The mainstream methods include Gabor filter method, active shape model ASM (Active Shape Models), principal component analysis PCA (Principal Component Analysis) and texture feature method. Gabor wavelet can extract the texture features of facial expressions from different scales and different directions, but the high dimensionality generated by the calculation process may lead to the exhaustion of computer memory, and the calculation process is quite time-consuming. The ASM algorithm can intuitively resp...

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