Facial expression recognition method based on rough set and mixed features

A technology of facial expression recognition and mixed features, which is applied in the field of facial expression recognition, can solve the problems of low recognition rate of facial expression recognition and long recognition time of facial expression recognition, and achieve high recognition rate, easy implementation, and short recognition time Effect

Inactive Publication Date: 2014-08-13
上海优思通信科技有限公司
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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for recognizing facial expressions, which is used to solve the problems that t...

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  • Facial expression recognition method based on rough set and mixed features
  • Facial expression recognition method based on rough set and mixed features
  • Facial expression recognition method based on rough set and mixed features

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Embodiment Construction

[0025] The present invention compares and learns from the existing successful facial expression recognition methods after extensively reading existing domestic and foreign literatures about facial expression feature extraction and facial expression recognition technology, and extracts and recognizes key technologies for corresponding human facial expression features To improve and perfect, at the same time put forward its own algorithm, improve the recognition rate of facial expression recognition, and shorten the recognition time of facial expression recognition.

[0026] see figure 1 Shown, implementing the facial expression recognition method of the present invention comprises the steps:

[0027] Step 1: Perform face detection;

[0028] Step 2: Extract the local geometric deformation features of expressions by using the method of combining active appearance model and rough set;

[0029] Step 3: Using the improved weighted principal component analysis method and rough set ...

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Abstract

The invention discloses a facial expression recognition method based on a rough set and mixed features. The method includes the following steps that (1) facial detection is carried out; (2) local geometric distortion features are extracted by means of a method combining an active appearance model and the rough set; (3) overall features of expressions are extracted with the combination of an improved weighting primary component analysis method and the rough set; (4) feature fusion is carried out on the extracted local geometric distortion features and the overall features by means of kernel canonical correlation analysis under a high-dimensional small sample to eliminate feature redundancy, and fused typical features are obtained; (5) the fused typical features serve as observation vectors of a discrete HMM for classification and recognition, and a classification result is obtained. As is presented by experiments, the improved method can shorten facial expression recognition time and improve the facial expression recognition rate.

Description

【Technical field】 [0001] The invention belongs to the technical field of computer information processing, in particular to a facial expression recognition method. 【Background technique】 [0002] Facial Expression Recognition (FER) is a process in which a computer extracts and classifies facial expression information. It is a very challenging subject interdisciplinary of pattern recognition, physiology, psychology, computer vision, etc. [0003] Although facial expression recognition technology has been studied by many people, the existing methods do not scatter and emphasize the information of the eyes, eyebrows, mouth and other areas of the face that make important contributions to expression changes, and a single feature extraction method cannot cover All the effective information does not take into account the importance of attribute features and the repetition of contributions to the information system, which leads to the low recognition rate of facial expression recogn...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 段丽钟晓乔亦民
Owner 上海优思通信科技有限公司
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