A facial expression conversion method based on identity and expression feature conversion

A technology of facial expressions and identity features, applied in the field of image processing, can solve problems such as difficult collection, limited number of subjects, and difficulty in distinguishing facial expressions and identity information, so as to enhance immersion and add fun

Inactive Publication Date: 2019-06-25
CENT SOUTH UNIV
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AI Technical Summary

Problems solved by technology

Researchers have strict requirements for the dataset, that is, facial images of the same person with different expressions, and some even require long-term paired samples, which are difficult

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  • A facial expression conversion method based on identity and expression feature conversion
  • A facial expression conversion method based on identity and expression feature conversion
  • A facial expression conversion method based on identity and expression feature conversion

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Embodiment Construction

[0026] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0027] The expression database used in the preferred embodiment of the present invention is the Extended Cohn-Kande data set (CK+), which is a complete facial expression data set. The dataset consists of 123 subjects with an age range of 18 to 50 and contains 593 image sequences. Most of the images in the dataset are grayscale images with a frontal view size of 640×490. Each sequence starts with a neutral expression image and ends with an extreme expression image. If a person has multiple sequences under the same expression type, only one sequence is selected for that person. The first and last frames of each sequence are extracted according to the label information as training data. Build 7 domains with the following attributes: Anger, Neutral, Disgust, Fear, Happiness, Sadness and Surprise.

[0028] according to figure 1 The shown block diagram o...

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Abstract

The invention provides a facial expression conversion method based on identity and expression feature conversion, and mainly solves the problem of personalized facial expression. Most of the existingfacial expression synthesis work attempts to learn conversion between expression domains, so that paired samples and marked query images are needed. Identity information and expression feature information of an original image can be stored by establishing the two encoders, and target facial expression features are used as condition tags. The method mainly comprises the following steps: firstly, carrying out facial expression training, preprocessing a neutral expression picture and other facial expression pictures, then extracting identity characteristic parameters and target facial expressioncharacteristic parameters of a neutral expression, and establishing a matching model; Secondly, performing facial expression conversion, inputting the neutral expression picture into a conversion model, and applying model output parameters to expression synthesis to synthesize a target expression image. Pairing data sets of different expressions with the same identity are not limited any more, identity information of an original image can be effectively reserved due to existence of the two encoders, and conversion from a neutral expression to different expressions can be achieved.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to a human facial expression conversion method based on identity and expression feature conversion. Background technique [0002] With the rapid development of computer technology, computers play an important role in human life. People also hope that computers can have human intelligence, and hope that computers can communicate with people unimpeded, and more natural human-computer interaction requires computers to have the ability to understand and express emotions, and to be able to adapt to the environment independently, which will fundamentally Changing the relationship between humans and computers, combining information such as facial expressions, voices, sights, and body postures can achieve more efficient and humanized human-computer interaction, and enable computers to better serve humans. Facial expression synthesis technology is an important aspect of computer simulation of ...

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Application Information

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IPC IPC(8): G06T3/00G06K9/00G06N3/04G06N3/08
Inventor 陈明义李长春李柯
Owner CENT SOUTH UNIV
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