Face alignment method based on thick-to-thin face shape estimation

A face alignment and face shape technology, applied in the field of computer vision, can solve the problem of low face alignment accuracy, and achieve the effect of improving the alignment effect and good robustness.

Inactive Publication Date: 2018-08-24
WUHAN UNIV
View PDF8 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0031] In order to solve the above-mentioned technical problems, the present invention proposes a face alignment method based on face shape estimation from coarse to

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
  • Face alignment method based on thick-to-thin face shape estimation
  • Face alignment method based on thick-to-thin face shape estimation
  • Face alignment method based on thick-to-thin face shape estimation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0046] The face alignment method based on coarse-to-fine face shape estimation is a simple but robust face alignment method. Using the coarse-to-fine face shape estimation method based on convolutional neural network can select the face shape with close additional attributes as the initialization shape with high accuracy, thereby reducing the dependence of the initialization shape on the average face and the enhancement algorithm on the face Robustness to differences in head pose, facial expression, occlusion, and lighting conditions improves the performance of the algorithm.

[0047] please s...

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 face alignment method based on thick-to-thin face shape estimation. As for any one input face image, firstly the initialized face shape is estimated and then the real shape of the face is gradually approximated, including estimation of the position of the main feature points of the face and the face expressions through the multitask deep learning framework, a head postureclassification model based on the convolutional neural network is constructed to perform accurate estimation and classification of the heat posture of the face, and the more accurate initialized shape is obtained by using the head posture classification result and the estimation result of the face expressions and the position of the main feature points; and the respective regressor is trained based on the initialized shape according to the classification result of the posture and the expressions and the face shape is updated so as to be approximate to the standard shape. The more accurate face initialized shape is constructed and the more advanced cascade regression framework is used so that the robustness of the face expressions, the head posture and the illumination shade difference canbe enhanced.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a face alignment method based on rough-to-fine face shape estimation in the field of face recognition of digital images. Background technique [0002] Face alignment can provide accurate and semantically specific face shape information, which can help realize geometric image normalization and feature extraction. Therefore, face alignment is an indispensable and important part of face recognition, facial posture and expression analysis, human-computer interaction and 3D face modeling. It is widely used in security, public security control, intelligent access control, human-computer interaction, assisted driving, Film and television production, video conferencing and other fields. In practice, the face alignment problem still faces great challenges due to differences in facial expressions, head poses, lighting conditions, and partial occlusions. Therefore, how...

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
CPCG06V40/168G06V40/172
Inventor 李晶万俊常军吴玉佳肖雅夫
Owner WUHAN UNIV
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