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Automatic facial expression recognition method

A technology for facial expression and automatic recognition, applied in character and pattern recognition, image analysis, instruments, etc., can solve problems such as poor robustness to illumination and noise, insufficient extraction of local information, long calculation time, etc.

Active Publication Date: 2020-12-22
HEBEI UNIV OF TECH +1
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a method for automatic recognition of human facial expressions, which is a method for automatic recognition of human facial expressions based on irregular segmentation of facial feature parts and multi-feature fusion. The facial expression recognition method has the disadvantages of poor robustness to light noise interference, insufficient extraction of local information, and complex calculations, resulting in low facial expression recognition rate and long calculation time.

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  • Automatic facial expression recognition method

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Embodiment 1

[0118] This embodiment is a method for automatic recognition of facial expressions based on irregular segmentation of facial feature parts and multi-feature fusion. The specific steps are as follows:

[0119] The first step, facial expression image preprocessing:

[0120] Using the following formula (1), the facial expression image collected from the USB interface of the computer is converted from the RGB space to the gray space, and then the size of the image is normalized to obtain the facial expression gray image I gray ,

[0121] I gray =0.299R+0.587G+0.114B (1),

[0122] In formula (1), R, G and B are the components of the red, green and blue channels respectively,

[0123] This completes the facial expression image preprocessing;

[0124] The second step is to automatically locate and mark the key feature points of the facial expression image:

[0125] Use the AAM algorithm to process the facial expression grayscale image I obtained in the first step above. gray Ac...

Embodiment 2

[0209] This embodiment is an experimental verification of a facial expression automatic recognition method based on irregular segmentation of facial feature parts and multi-feature fusion adopted in the present invention.

[0210] In this embodiment, experiments have been carried out on the JAFFE facial expression database and the CK+ facial expression database. Among them, the JAFFE database has a total of 213 facial expression images, which are composed of seven facial expressions of ten women, including neutrality, happiness, sadness, anger, surprise, fear and disgust. 137 facial expression images in the JAFFE database are selected as training data, and the remaining 76 facial expression images are used for testing. The CK+ facial expression database contains 123 participants from different countries and regions, and a total of 593 facial expression sequences. Each facial expression sequence starts with a neutral facial expression and ends with a peak frame of facial expres...

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Abstract

The invention discloses an automatic recognition method for facial expressions. The method relates to image preprocessing for extracting image features or characteristics of an identification graph, and comprises the following steps of: performing automatic positioning marking on key feature points of a facial expression image by the facial expression image preprocessing to form feature blocks from the key feature points of the facial expression image so as to obtain PD-of each irregular polygon feature block; an LDN feature histogram; seven-order moment features of each irregular polygonal feature block are obtained, and PD-is obtained. And the LDN feature histogram and the seven-order moment feature are fused together to obtain fused facial expression feature data, and the SVM classifieris adopted to train and predict the facial expression, so that the automatic recognition of the facial expression is realized. The method disclosed by the invention overcomes the defects of low facial expression recognition rate and overlong calculation time caused by poor interference robustness on illumination noise, insufficient extraction of local information and complex calculation in the existing facial expression recognition method.

Description

technical field [0001] The technical solution of the present invention relates to image preprocessing for extracting image features or characteristics for recognition graphics, specifically a method for automatic recognition of human facial expressions. Background technique [0002] Facial expression recognition belongs to the category of emotion recognition, which refers to assigning an emotion category to a given face image, including happiness, sadness, fear, surprise, anger, or disgust. Automatic facial expression recognition is the focus of research in the field of computer vision. [0003] The technologies involved in the automatic facial expression recognition method include facial expression image acquisition, facial image preprocessing, facial image feature extraction and facial expression classification, wherein facial image feature extraction is a part of the automatic facial expression recognition process. An important link, its effectiveness determines the accu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06T7/13G06T7/40G06T7/90
Inventor 于明高磊王岩刘依于洋师硕郭迎春郝小可朱叶阎刚
Owner HEBEI UNIV OF TECH
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