System and method for multi-dimensional emotion discrimination of face image based on neural network

Abstract

The present invention provides a system and method for multi-dimensional emotion discrimination of a face image based on a neural network. The system comprises: a face location module configured to identify a face region in an image to be detected and extract a face image in the image to be detected; a feature extraction module configured to extract emotion features of the face image; an identification module configured to identify the emotion features to obtain emotion information; and an output module configured to output the emotion information. The system and method for multi-dimensional emotion discrimination of the face image based on the neural network can adapt different face angles, skin colors and face shapes to extract emotion feature vectors and represent the multi-dimensional emotion to which the face image belongs so as to improve the accuracy of face emotion analysis.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a neural network-based multi-dimensional emotion discrimination system and method for human face images. Background technique [0002] People use facial expressions, gestures, body and language to convey information and communicate. Recognizing facial emotions is one of the most direct ways to understand the information conveyed by human beings. The traditional field of facial emotion recognition mainly includes the following aspects: [0003] Emotion recognition of key point detection: Identify the area where the face is located, use the traditional algorithm to locate the key points of the face, facial features and contours, and extract key point features as the features of emotion recognition. The method is limited by the accuracy of key point positioning, and only human The contour of the face lacks the changes of facial muscles. This method is too gener...

AI Technical Summary

Problems solved by technology

[0003] Emotion recognition of key point detection: Identify the area where the face is located, use the traditional algorithm to locate the key points of the face, facial features and contours, and extract key point features as the features of emotion recognition. The method is limited by the accuracy of key point positioning, and only human Face contour, lack of changes in facial muscles, this way is too general, and it is difficult to accurately identify emotions

[0004] On the other hand, the classification of emotion recognition: human emotion changes are difficult to explain in discrete categories. For example, anger and sadness are not separated by a thin line. Human emotions are mixed and continuous. An expression of emotion, such a method is too general and cannot describe people's delicate emotions carefully

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