Fuzzy discriminant analysis method applied to facial expression recognition

A technique of discriminant analysis and facial expression, applied in character and pattern recognition, computer components, instruments, etc., can solve problems such as immaturity of canonical correlation analysis

Inactive Publication Date: 2010-01-06
邹采荣 +1
View PDF0 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Some current methods do not effectively solve these problems, and the research method of applying the fuz

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
  • Fuzzy discriminant analysis method applied to facial expression recognition
  • Fuzzy discriminant analysis method applied to facial expression recognition
  • Fuzzy discriminant analysis method applied to facial expression recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] The technical solutions of the present invention will be further described below in conjunction with the drawings and embodiments.

[0042] 1. Use fuzzy K-nearest neighbors to specify class membership

[0043] First, for each training sample x i Create a class membership vector s associated with it ij (j=1, 2, . . . , c). Here, the Fuzzy K-Nearest Neighbor (Fuzzy K-NN) method is used to solve the class membership vector. Since the fuzzy K-NN method needs to define a distance metric to calculate the class membership of each data point, let the distance between two points x and y be, namely:

[0044] d ( x , y ) = | | x - y | | = ( x - y ) T (...

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 proposes a fuzzy discriminant analysis method applied to facial expression recognition. Category membership of each training sample is designed by adopting a fuzzy K nearest neighbor method (Fuzzy KNN); on the basis, a canonical correlation analysis (CCA) method is applied to finding a solution so as to enable the training samples and the corresponding fuzzy category membership thereof to have the projection direction of maximum correlation; relation between input data and corresponding category membership data is established by adopting a least-squares regression (LSR) method; and then category indexes are established according to the category membership data. In order to improve recognition results, the method can be spread to nuclear space through kernel functions. The method provides an effective means to estimate the degree of the possibility that a to-be-tested sample belongs to a certain category, and solves the problem that a large number of actual facial-expression samples cannot be simply attributed to a certain category. Experiments show that the method has better recognition performance compared with the prior expression recognition method.

Description

technical field [0001] The invention relates to a fuzzy discriminant analysis method, in particular to a fuzzy discriminant analysis method applied to facial expression recognition. Background technique [0002] At present, the linear discriminant analysis (LDA) method has been successfully applied to many pattern recognition problems, such as face recognition, image restoration, facial expression recognition and so on. Traditional discriminant analysis methods require each training sample to uniquely belong to a certain category of pattern types. However, in practice, some pattern samples cannot simply be assigned to a certain category. In this case, the traditional discriminant analysis method can no longer be well applied. For example, when doing facial expression recognition, each facial image may contain information about all six basic expressions (happy, sad, surprised, angry, disgusted, and scared). Therefore, it is unreasonable to simply classify each face image i...

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): G06K9/00
Inventor 邹采荣周晓彦赵力郑文明魏昕
Owner 邹采荣
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