Portrait generation method based on face structure information

A face structure and portrait technology, applied in neural learning methods, biological neural network models, instruments, etc., can solve the problems of identity information feature extraction and retention, face identity information retention and other problems

Active Publication Date: 2018-09-28
HANGZHOU DIANZI UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the extraction and retention of identity information features is still a difficult problem in the actual sketch gene

Method used

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  • Portrait generation method based on face structure information
  • Portrait generation method based on face structure information
  • Portrait generation method based on face structure information

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Experimental program
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Embodiment Construction

[0064] The detailed parameters of the present invention will be further specifically described below.

[0065] Such as figure 1 As shown, a portrait generation method based on face structure information includes the following steps:

[0066] Step (1), data preprocessing:

[0067] Face alignment is performed on face photos and portraits with the original size of 250×200. The image size of the aligned face photos is 250×200, the distance between the eyes is 50, and the distance from the eyes to the top of the image is 125; Fill the edge of the image to get a 286×286 image, randomly select a face photo image X of size 256×256 each time for training; use the U-Net network to extract features with spatial and texture information;

[0068] The aligned face photo image X corresponds to the sketch image Y of the face photo and the probability map of the face structural components Form the triplet, X, Y, as a training set;

[0069] Step (2), based on the probability map of face ...

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Abstract

The invention discloses a portrait generation method based on the face structure information. The method comprises the following steps: 1, carrying out data preprocessing on an original image, a target image and the face structure information; 2, carrying out feature extraction and feature fusion at the input end of an image generator through a face structure information model; 3, adopting a combination loss function based on face structure components for the loss function part of the image generator; 4, generating a countermeasure network by using the generator, and distinguishing by using adiscriminator; 5, carrying out model training, and training neural network parameters through a reverse propagation algorithm. According to the invention, a neural network model generated from a facephoto to a portrait is provided. The invention particularly provides a method for carrying out network parameter optimization by utilizing the guidance information of a face part through a portrait generator to generate a portrait and calculating the loss of each part by means of the part information so as to optimize network parameters. Based on the method, the best effect in the generation fieldof face photos and portraits is obtained.

Description

technical field [0001] The present invention relates to a generation confrontation network generated from a face photo to a portrait (Photo-Sketch Synthesis), which mainly relates to a method for modeling from a face photo-portrait generation, and using face structure information to image The generation of the guided optimization. Background technique [0002] Face sketch portrait generation (Sketch Portrait Generation) problem is to generate a corresponding face sketch given a face, and it is also called photo-sketch transformation (Photo-sketch Transformation) or face sketch generation (Face Sketch Synthesis). Face sketch generation has many applications, such as entertainment or criminal investigation. An ideal generated face sketch should have two characteristics, one is to retain the appearance of the person, so that there is a high readiness rate in the recognition of the identity information of the sketch face sketch; the other is to be like a sketch, so that it It...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/08
CPCG06N3/084G06V40/171
Inventor 俞俊施圣洁高飞
Owner HANGZHOU DIANZI UNIV
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