Method for positioning facial features based on improved ASM (Active Shape Model) algorithm

A technology of facial features and localization methods, which is applied in the fields of computer vision and image processing, and can solve problems such as unsatisfactory localization effects.

Inactive Publication Date: 2011-10-12
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF3 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This patent accelerates the standardized alignment operation of training samples. Although the operati

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
  • Method for positioning facial features based on improved ASM (Active Shape Model) algorithm
  • Method for positioning facial features based on improved ASM (Active Shape Model) algorithm
  • Method for positioning facial features based on improved ASM (Active Shape Model) algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] In the realization process of the present invention, at first, the realization and simulation of the algorithm are carried out based on the Matlab platform.

[0050] During the model building process, 240 images of 40 people in the imm_face_db face database, including illumination changes, expression changes and pose changes, were used as sample images for model building. In the feature point calibration process, the upper model contains 37 calibration points, and the lower model contains 23 calibration points. The final average shape and eigenvectors of the upper model are both 74*1-dimensional vectors, of which 16 are required for the eigenvectors; the average shape and eigenvectors of the obtained lower model are both 46*1-dimensional vectors, of which 12 are required for the eigenvectors . Select 5 pixel values ​​on both sides of each feature calibration point, and the obtained local grayscale model is a 10*1-dimensional vector.

[0051] During the matching search...

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 method for positioning facial features based on an improved ASM (Active Shape Model) algorithm, belonging to the technical field of visual and image treatment of a computer. The method comprises the following steps of: firstly, manually calibrating feature points; secondly, establishing a statistical shape model and a local gray model of an upper model and a lower model; thirdly, separately searching and matching the feature points in the upper model and the lower model; and finally, generating an example of a comprehensive model restrained by an energy function. To solve the problem that the traditional ASM method is difficult to position features under the facial expression conditions of a human face, the method for positioning facial features based on the improved ASM algorithm, disclosed by the invention, comprises the following steps of: carrying out the regional division of the facial features into an upper shape region and a lower shape region according to the change correlation, separately modeling the statistical shape model and the local gray model, generating examples of comprehensive shapes for the upper model and the lower model to restrain errors by introducing an energy function to the feature matching and searching process, and finally, obtaining an accurate feature positioning result. Due to the method for positioning facial features based on the improved ASM algorithm, the feature positioning accuracy of the ASM algorithm to the existing facial expression conditions are further improved.

Description

[0001] The invention belongs to the technical field of computer vision and image processing, and mainly relates to a face recognition technology in biometric identification, in particular to a face feature positioning method based on an ASM algorithm. Background technique [0002] In recent years, with the rapid development of information technology, how to quickly and accurately identify a person's identity to ensure information security and public safety has become a key technical problem that needs to be solved urgently. For this reason, biometric identification technology emerged as the times require and has become a mainstream research topic in the field of information security in the world. Biometric identification technology uses the inherent physiological structure and behavioral characteristics of the human body for personal identification. As an important branch of biometric recognition technology, face recognition technology, combined with computer vision and image ...

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 解梅魏云龙
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