Expression recognition method and device based on local image data fusion

Abstract

The invention provides an expression recognition method and device based on local image data fusion. The method comprises the following steps: acquiring a grayscale image and a depth image containing a target face; the grayscale image is preprocessed, and the image mouth length of the target face is further determined; comparing the mouth length of the image with a reference mouth length corresponding to the target face, and determining a comparison result; based on the comparison result, an accurate fusion region and a rough fusion region are determined, and both the accurate fusion region and the rough fusion region belong to partial regions in the target face; based on the precise fusion region and the rough fusion region, carrying out precision-differentiated image fusion on the preprocessed grayscale image and the preprocessed depth image; and performing expression recognition on the fused face image, and determining the expression of the target face at the moment. Therefore, the accuracy and the stability of facial expression recognition can be improved.

Description

technical field [0001] The present application relates to the technical field of face recognition, in particular, to an expression recognition method and device based on partial image data fusion. Background technique [0002] In the field of human-computer interaction, accurate recognition of human facial expressions can help machines and computers recognize possible human cognition and thinking patterns, thereby accurately understanding human emotions and improving the quality of human-computer interaction. Facial expression data is high-dimensional and complex data, and the data describing facial expressions has a large spatial dimension. [0003] At present, the expression recognition method based on the grayscale image of the face is easily affected by the change of illumination; while the expression recognition method based on the depth image of the face is easily affected by the accuracy of data collection and dynamic changes (such as dynamic changes of facial feature...

AI Technical Summary

Problems solved by technology

[0003] At present, the expression recognition method based on the grayscale image of the face is easily affected by the change of illumination; while the expression recognition method based on the depth image of the face is easily affected by the accuracy of data collection and dynamic changes (such as dynamic changes of facial features, changes in positions, etc.) ) and other factors hinder the stability and accuracy of the facial expression recognition system

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