Facial expression recognition method based on random forests

A facial expression recognition, random forest technology, applied in the field of facial expression recognition, can solve problems such as unsatisfactory effect, changeable, complex facial expression, etc.

Inactive Publication Date: 2015-02-25
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF4 Cites 36 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

(3) Facial expressions are complex and changeable
(4) Susceptible to factors such as posture and illumination
Although facial expression recognition has been studied for a long time and many soluti...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Facial expression recognition method based on random forests
  • Facial expression recognition method based on random forests
  • Facial expression recognition method based on random forests

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] A method for facial expression recognition based on random forest includes the following steps:

[0054] Step 1 AAM displacement feature extraction

[0055] AAM is based on the Active Shape Model (ASM), which was originally proposed by Edwards, Cootes, and Taylor. AAM includes two parts: shape model and texture model. The present invention uses a shape model. The shape model is defined as the coordinates of n feature points:

[0056] s=(x 1 ,y 1 ,x 2 ,y 2 ,...,X n ,y n ) T

[0057] It can be turned into a linear model:

[0058] s = s 0 + X i = 1 n p i s i

[0059] Where p i Is the shape parameter, s i It is obtained through PCA (Principal Component Analysis) dimensionality reduction on the training data. However, for calculation and tracking considerations, the present invention does not adopt the second expression mode, but adopts the first simple expression form. See the detailed process figure 2 .

[0060] Step 1.1 Select the first...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a facial expression recognition method based on random forests. The facial expression recognition method based on the random forests comprises the step of extraction of a displacement feature of an AAM, the step of extraction of AUs in a facial expression sequence, the step of training of a facial expression classification model and the step of facial expression recognition. According to the facial expression recognition method, the novel AAM displacement feature is provided to be used for training and learning the AUs, and finally facial expression recognition is carried out by depending on the AUs. Compared with other feature representations in identification of the same classification, the facial expression recognition method based on the random forests better describes expression information and changing process information contained in the expression sequence. The random forests are used for facial expression recognition for the first time, and the random forests in the method have a better classified recognition effect in the field compared with a frequently used support vector machine (SVM) method at present. For the aspect of CK and AU recognition of databases, the facial expression recognition method based on the random forests can achieve a perfect recognition effect.

Description

Technical field [0001] The invention relates to a face expression recognition method, in particular to a face expression recognition method based on random forest. Background technique [0002] Facial expressions, as important non-verbal information, can provide very rich information and effectively supplement language communication. A person's emotions are often directly reflected in facial expressions. Let the computer automatically recognize facial expressions, which is conducive to the computer to better interact with people and provide humanized services. Facial expression recognition can be widely used in many fields, such as medical treatment, human-computer interaction (HCI), video games, data-driven animation, etc. In the past two decades, facial expression recognition has attracted more and more research attention, and a variety of advanced algorithms have been proposed. [1] . Facial expressions have the following characteristics: (1) Subtlety. This is reflected in ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/66G06K9/46
CPCG06V40/176G06F18/21
Inventor 蒲晓蓉陈雷霆王耀晖蔡洪斌陈雄曹跃崔金钟卢光辉邱航
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap