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Automatic facial expression recognition method based on multi-feature fusion
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A multi-feature fusion, facial expression technology, applied in the field of recognizing graphics, can solve the problems of low recognition rate, full use of local information and overall information, and poor robustness.
Inactive Publication Date: 2020-03-27
HEBEI UNIV OF TECH
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[0005] The technical problem to be solved by the present invention is to provide an automatic facial expression recognition method based on multi-feature fusion, which is a method for fusing Gabor features and multi-scale ACILBP feature histograms of facial expression images and facial expression important region images, It overcomes the shortcomings of the existing facial expression recognition methods, which generally have poor robustness to illumination and noise, and do not consider the full use of local information and overall information, resulting in low recognition rates
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Embodiment 1
[0072] The facial expression automatic recognition method based on multi-feature fusion of the present embodiment is a method of fusing Gabor features and multi-scale ACILBP feature histograms of facial expression images and facial expression important region images, and the specific steps are as follows:
[0073] The first step is preprocessing of facial expression images and images of important areas of facial expressions:
[0074] (1.1) Geometric normalization of facial expression images:
[0075] Input the RGB image of the face into the computer through the USB interface, and use the formula (1) to convert it into a grayscale image O,
[0077] Among them, R, G and B are the three channels of red, green and blue respectively, and (x, y) are the pixel coordinates of the image. For the obtained grayscale image O, the DMF_Meanshift algorithm is used to detect the key points of the face, and the eyes, The center poin...
Embodiment 2
[0127] In order to verify the advantages of the method of the present invention in the automatic recognition rate of human facial expressions, this embodiment selects six widely used facial expression recognition methods and compares them with the automatic recognition method of human facial expressions based on multi-feature fusion of the present invention, The six facial expression recognition methods are: Orthogonal Combination OfLocal Binary Patterns (OCLBP), Symmetric Local Graph Structure (Symmetric Local Graph Structure, SLGS), Noise-resistant Local Binary Pattern (Noise-resistant Local Binary Patterns, NRLBP), Strong Robust Local Binary Pattern (Completed Robust Local Binary Pattern, CRLBP), Local Mesh Patterns (LocalMesh Patterns, LMep), Joint Local Binary Patterns (JLBP).
[0128] Utilize the SVM classifier to carry out comparative experiments on the JAFFE and CK databases, wherein the selection mode of the training samples is random selection. In the present embodime...
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Abstract
The present invention is based on the facial expression automatic recognition method of multi-feature fusion, relates to the method for recognizing figure, is a kind of fusion facial expression image and the Gabor feature of human facial expression important region image and the method of multi-scale ACILBP characteristic histogram, the step is : Preprocessing of facial expression images and images of important areas of facial expression; Gabor features are extracted from facial expression images and images of important areas of facial expression respectively, and given different weights, and Gabor features of two layers of facial expression images are obtained by fusion; The ACILBP operator is used to extract multi-scale ACILBP feature histograms; feature fusion is used to obtain facial expression feature data; SVM classifier is used to train and predict facial expressions to realize automatic recognition of facial expressions. The invention overcomes the disadvantages of poor robustness to illumination and noise generally existing in the prior art, and low recognition rate due to lack of full utilization of local information and overall information.
Description
technical field [0001] The technical solution of the present invention relates to a method for recognizing graphics, in particular to a method for automatic recognition of human facial expressions based on multi-feature fusion. Background technique [0002] Human language is divided into two categories: natural language and body language, and facial expressions are part of body language. Psychologists have found that when human beings communicate in a conversation: the language content accounts for 7%; the tone of speech accounts for 38%; and the speaker's expression accounts for 55%. Therefore, facial expressions play an important role in human communication activities. Corresponding expression recognition has always been a very active hotspot in the field of pattern recognition and computer vision. With the development of artificial intelligence and pattern recognition, facial expression recognition has received increasing attention, and its position in human-computer in...
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