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Expression recognition method based on AVR and enhanced LBP

An expression recognition and image technology, applied in the field of pattern recognition technology, can solve the problems of small number of features, high expression recognition results, and suboptimal selection of classifiers, etc.

Inactive Publication Date: 2009-12-30
SHANGHAI JIAO TONG UNIV +1
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Problems solved by technology

This method only extracts the LBP features of an image, the number of features is too small, the selection of the classifier is not optimal, and the expression recognition result is not very high, the highest is only 87.86%

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  • Expression recognition method based on AVR and enhanced LBP
  • Expression recognition method based on AVR and enhanced LBP
  • Expression recognition method based on AVR and enhanced LBP

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Embodiment Construction

[0039] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0040] Such as figure 1 As shown, this embodiment includes the following steps:

[0041] The first step is to collect the original image: the face image in the color space is collected by the video capture device, and then the face detection is performed on the image collected by the camera through the face detector, and the detected face image is saved. The human face image is divided into blocks, and the human eye detection is performed on the two upper left and upper right images respectively through the human eye detector to identify the position of the human eye; then the two-dimensional model is used to cut ...

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Abstract

An expression recognition method based on AVR and enhanced LBP in the technical field of model recognition comprises the following steps: collecting an original image; expanding virtual samples; carrying out wavelet decomposition on human image; extracting local binary pattern characteristic LBP; calculating an enhanced variance ratio AVR characteristic value and adding with a penalty factor, then extracting a plurality of groups of characteristic values of different dimensionality discriminated by AVR value, carrying out support vector machine classification accuracy test, and taking the characteristic dimensionality with the highest accuracy and corresponding characteristic value as the LBP characteristic. The method of the invention integrates image acquisition, human face test and human eye test, enhances the LBP characteristic by wavelet decomposition, and effectively improves the accuracy by adopting AVR method to extract effective characteristic.

Description

technical field [0001] The invention relates to a recognition method in the technical field of pattern recognition, in particular to an expression recognition method based on AVR and enhanced LBP. Background technique [0002] The facial expression of the human face is an important way for human beings to communicate emotionally. Through the exchange of expressions, people can perceive each other's emotional changes and emotional fluctuations. With the development of computer vision technology, facial expression recognition has played an important role in many fields such as friendly human-computer interaction, two-dimensional and three-dimensional facial animation, psychology and cognition. Facial expression recognition is based on visual information to classify the movement of the face and the deformation of facial features, mainly including face detection, facial feature extraction and expression classification, among which feature extraction and classification are the fo...

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62
Inventor 陈晓光陈刚申瑞民张怡
Owner SHANGHAI JIAO TONG UNIV
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