Face image real-time beautifying and texture synthesizing method

A texture synthesis, face image technology, applied in image data processing, image enhancement, image analysis and other directions, can solve problems such as large amount of calculation, image blur, local blur, etc., to achieve the effect of superior computing efficiency

Inactive Publication Date: 2019-09-03
ZHEJIANG SCI-TECH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among them, the weighted average method is simple and the calculation speed is fast, but the fusion effect is poor, and it is difficult to eliminate the blurred shadows formed by the moving target; the Gaussian filtering method uses the Gaussian kernel function to smooth the image overlapping area, which is easy to cause local blurring; multi-resolution The method decomposes the image in different frequency bands to realize the fusion transition of the whole image, but it needs multiple filtering, and the calculation amount is large, which will easily cause the signal to weaken and cause the image to be blurred; the method based on the gradient domain realizes the synthesis of the image in the gradient domain. The gradient information of the known image guides the interpolation fusion, there will be no blurring phenomenon, and the fusion effect is good

Method used

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  • Face image real-time beautifying and texture synthesizing method
  • Face image real-time beautifying and texture synthesizing method
  • Face image real-time beautifying and texture synthesizing method

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Experimental program
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Effect test

Embodiment 1

[0056] According to attached figure 1 Shown flow chart, a kind of face image real-time beautification and texture synthesis method are characterized in that comprising the following steps:

[0057] (1) Use the ASM algorithm to extract face feature points

[0058] Establish an active shape model and a local grayscale model; match the initial shape to the target image, and adjust it according to the local grayscale model until convergence; the detected feature points select the area composed of eyebrows, eyes, nose, and mouth as the area to be fused area;

[0059] In this application, the ASM algorithm is used to extract facial feature points. The ASM algorithm realizes feature point extraction through two steps of model training and model search. In the model training stage, the active shape model and local grayscale model are established for the training sample set; in the model search stage, the initial shape obtained in the first step is matched to the target image, and t...

Embodiment 2

[0079] In the process shown in embodiment 1, the method used in the local color conversion process in step (2) in the above-mentioned a kind of face image real-time beautification and texture synthesis method is as follows:

[0080] First, while mapping the data from high-dimensional to low-dimensional, while keeping the data manifold structure unchanged, use the vector x i To represent a pixel point i in a certain feature space; given a data set x 1 ,...,x N , for each pixel x i , select its k nearest neighbors, expressed as will calculate a set of weights ω ij make

[0081] The k neighbors can best reconstruct the pixel x i , calculated by minimizing the energy function

[0082]

[0083] Restrictions obtain after, with x i x i The linear combination of neighborhoods can reconstruct x i x i ;

[0084] Secondly, the method of edit propagation will be used to realize the color conversion; given the original image and the target image, the color is transferr...

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Abstract

The invention discloses a model construction method, and particularly relates to a face image real-time beautifying and texture synthesizing method for three-dimensional face reconstruction. Accordingto the method, through the processes of face feature point extraction by utilizing an ASM algorithm, color conversion, face seamless fusion, eyebrow repair processing, three-dimensional face reconstruction and the like, the automatic detection and beautification can be realized on the face, so that a relatively better face reconstruction result is obtained. Experimental results show that the algorithm provided by the invention can obtain a satisfactory reconstruction effect, including reconstructing a shielded eyebrow region, has the superior operation efficiency compared with other methods,and can achieve the real-time performance. The face image is beautified based on the standard skin color to generate the face texture map, and the face texture map is applied to the three-dimensionalface reconstruction to obtain the personalized three-dimensional face model.

Description

technical field [0001] The invention relates to a model construction method, in particular to a face image real-time beautification and texture synthesis method for three-dimensional face reconstruction. Background technique [0002] In recent years, face image texture synthesis and 3D face reconstruction have become research hotspots in the fields of image processing, computer vision, artificial intelligence and pattern recognition. Image-based 3D face reconstruction has a wide range of application values ​​in 3D animation, computer games, virtual clothing fitting and other fields because it can enhance the user's experience. [0003] At present, image-based 3D face reconstruction can be divided into reconstruction based on depth images, reconstruction based on multiple image sequences, and reconstruction based on single images. 3D face reconstruction based on a single image has become a hot research direction in face reconstruction because it uses less face photos and is ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/90G06K9/00
CPCG06T5/008G06T5/005G06T7/90G06V40/168
Inventor 李重刘恒任义阳策
Owner ZHEJIANG SCI-TECH UNIV
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