Feature classification based multiple classifiers combined people face recognition method

A face recognition and multi-classifier technology, applied in the field of face recognition, can solve the problems of classification information loss, system recognition performance degradation, etc., to improve recognition performance, avoid dimension disaster problems, and reduce computational complexity.

Active Publication Date: 2007-02-07
INST OF COMPUTING TECH CHINESE ACAD OF SCI
View PDF0 Cites 49 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the disadvantages of the prior art that high-dimensional feature dimensions need to be reduced in dimensionality, which may easily

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
  • Feature classification based multiple classifiers combined people face recognition method
  • Feature classification based multiple classifiers combined people face recognition method
  • Feature classification based multiple classifiers combined people face recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The method of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0028] Such as figure 1 Shown, the multi-classifier combined face recognition method based on feature grouping of the present invention comprises:

[0029] Step 10, extracting the face area, and performing preprocessing on the face area. Generally, the original image with a human face cannot be used directly. The proportion of the human face area in the original image is small, and the original image will be affected by noise, pose, lighting, etc. In order to improve the effect of face recognition, the face area must be extracted from the original image before recognition. When extracting the face area, according to the binocular position given by the face detection and feature location algorithm, the face to be recognized is cut out from the input image, and the size and range of the cut face are determined by the specific fa...

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 disclosed multi-classifier combination face recognition method based on feature sorting comprises: extracting face area from initial image for pre-process and feature extraction; feature sorting to obtain different face feature groups; designing component classifier for every group to recognize face and combine results for optimal effect. This invention overcomes dimension disaster, reduces algorithm complexity, and improves recognition performance.

Description

technical field [0001] The present invention relates to face recognition technology, in particular to feature grouping and multi-component classifier combination face recognition technology. Background technique [0002] The purpose of face recognition technology is to give computers the ability to identify people based on their faces. As a scientific problem, face recognition is a typical image pattern analysis, understanding and classification calculation problem, which involves pattern recognition, computer vision, intelligent human-computer interaction, graphics, cognitive science and other disciplines. As one of the key technologies of biometric identification, face recognition technology has potential application prospects in public security, information security, finance and other fields. [0003] In face recognition technology, efficient face description features and corresponding high-precision core recognition algorithms are the key to the problem. The input of t...

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 山世光苏煜曹波陈熙霖高文
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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