Facial expression analysis method based on feature points and local features

Abstract

The invention discloses a facial expression analysis method based on feature points and local features, belongs to the technical field of facial expression analysis, and aims to solve the technical problem of how to predict facial expressions through multi-feature combination and improve the prediction accuracy. The method comprises the following steps: extracting coordinate values of face key points, and performing reduction and clipping processing on a face image based on the coordinate values of the face key points to obtain feature points; for each preprocessed face image, face parts are extracted based on the coordinate values of the face key points; dividing each face part into a plurality of face sub-regions, extracting a local binary pattern from each face sub-region to obtain a row vector, and splicing each face image and each preprocessed face image with the corresponding row vector to obtain a row vector; forming a feature matrix as a local feature based on all row vectors corresponding to the face image data set; and carrying out support vector machine classification to train a support vector machine, and carrying out expression prediction through the trained support vector machine.

Description

technical field [0001] The invention relates to the technical field of facial expression analysis, in particular to a facial expression analysis method based on feature points and local features. Background technique [0002] In the process of social communication, in addition to intuitively understanding what the other party wants to express through language, you can also see potential information through facial expressions, and this potential information is the real meaning that most people want to express , emotion prediction plays an important role in the process of communication. Facial expressions can reflect people's emotions, so the emotional state can be predicted by predicting facial expressions. [0003] Human-computer interaction means that humans and machines can exchange information in certain ways. The purpose of human-computer interaction is to serve humans, so machines need to understand the potential information expressed by facial expressions. If the mac...

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