CN109409274B - Face image transformation method based on face three-dimensional reconstruction and face alignment - Google Patents
Face image transformation method based on face three-dimensional reconstruction and face alignment Download PDFInfo
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Abstract
A face image transformation method based on face three-dimensional reconstruction and face alignment adopts the following steps, step 1: the three-dimensional image acquisition device acquires a three-dimensional image of a human face as an input image and transmits the input image to the processing module; step 2: extracting three-dimensional characteristics of the input image by a face recognition module; the three-dimensional features of the input image comprise coordinate values of a face feature point set; storing a standard face alignment feature set in a standard face database, wherein the face alignment feature set is composed of face alignment feature points, and each face alignment feature point is semantic information of a corresponding point on a face; and step 3: the human face recognition system is provided with a reference picture database, and a processing module extracts a reference picture from the reference picture database and transmits the reference picture to the human face recognition module. The human face image transformation method based on human face three-dimensional reconstruction and human face alignment can adapt to various postures and expressions, and effectively maps large posture and expression changes which cannot be processed by the traditional method. The method can also process all human faces by using a universal model, and overcomes the defects of the GAN method.
Description
Technical Field
The invention relates to the field of image processing, in particular to a human face image transformation method based on human face three-dimensional reconstruction and human face alignment.
Background
With the rise of artificial intelligence trend, especially the large-scale research and application of the deep learning technology in the image field, the reconstruction of the three-dimensional structure of the human face and the alignment of the human face have better and better effects, for example, the accuracy and the speed of pr _ net proposed recently all reach practical requirements.
In the field of entertainment and games, there are many demands for changing one face to another image or editing the face image, such as synthetic ancient style or national photos popular with WeChat friends, synthetic admission notice books, etc.; in the process of post-processing of art photos, the expression of the face needs to be finely adjusted; in a game or animation, a human face needs to be attached to a model or a human face corresponding to an actor.
The traditional face fitting is based on key points, triangulation is carried out according to the key points, and then each triangle is subjected to mapping transformation. This approach can only deal with frontal faces, and is not applicable to situations where a human face has a large pose angle.
With the rise of deep learning technology, some GAN-based face mapping technologies have appeared. For example, the technology based on GAN can map faces with various postures and expressions, and can achieve good effect in a specific scene. But what is learned based on GAN is not the way in which the map is attached, but rather the features of the particular face that is learned. This requires that the corresponding model be trained for each specific face, and a generic model cannot be used, which is difficult to implement in many scenarios.
Disclosure of Invention
The invention provides a face image transformation method based on face three-dimensional reconstruction and face alignment, aiming at the defects of the prior art, and the specific technical scheme is as follows:
a face image transformation method based on face three-dimensional reconstruction and face alignment is characterized in that:
the following steps are adopted for the preparation of the anti-cancer medicine,
step 1: the three-dimensional image acquisition device acquires a three-dimensional image of a human face as an input image and transmits the input image to the processing module;
step 2: extracting three-dimensional characteristics of the input image by a face recognition module;
the three-dimensional features of the input image comprise coordinate values of a face feature point set;
storing a standard face alignment feature set in a standard face database, wherein the face alignment feature set is composed of face alignment feature points, and each face alignment feature point is semantic information of a corresponding point on a face;
and step 3: a reference picture database is arranged, and a processing module extracts a reference picture from the reference picture database and transmits the reference picture to a face recognition module;
the face recognition module extracts the three-dimensional features and the face alignment feature set of the reference picture and stores the three-dimensional features and the face alignment feature set of the reference picture in a temporary database;
and 4, step 4: the processing module maps the input image and maps the texture of the input image to the corresponding position of a reference image;
specifically, a processing module extracts three-dimensional features of an input picture to obtain textures of corresponding positions;
acquiring a corresponding three-dimensional coordinate point set of a reference picture according to a face alignment feature set of an input picture;
and 5: and the processing module assigns the texture acquired from the input picture to the corresponding coordinate in the three-dimensional coordinate point set of the reference picture in an interpolation mode.
Step 6: the processing module fuses the face picture into the reference picture through Poisson and replaces the face in the reference picture.
Further: and step 6, the processing module fuses the face picture into the reference picture through an alpha channel.
The invention has the beneficial effects that: the human face image transformation method based on human face three-dimensional reconstruction and human face alignment can adapt to various postures and expressions, and effectively maps large posture and expression changes which cannot be processed by the traditional method. The method can also process all human faces by using a universal model, and overcomes the defects of the GAN method. In addition, the method can also achieve the effect of real-time operation while ensuring the precision, and can be effectively applied to actual scenes.
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FIG. 1 is a flow chart of the operation of the present invention.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, will make the advantages and features of the invention easier to understand by those skilled in the art, and thus will clearly and clearly define the scope of the invention.
As shown in fig. 1: a human face image transformation method based on human face three-dimensional reconstruction and human face alignment,
the following steps are adopted for the preparation of the anti-cancer medicine,
step 1: the three-dimensional image acquisition device acquires a three-dimensional image of a human face as an input image and transmits the input image to the processing module;
step 2: extracting three-dimensional characteristics of the input image by a face recognition module;
the three-dimensional features of the input image comprise coordinate values of a face feature point set;
storing a standard face alignment feature set in a standard face database, wherein the face alignment feature set is composed of face alignment feature points, and each face alignment feature point is semantic information of a corresponding point on a face;
and step 3: a reference picture database is arranged, and a processing module extracts a reference picture from the reference picture database and transmits the reference picture to a face recognition module;
the face recognition module extracts the three-dimensional features and the face alignment feature set of the reference picture and stores the three-dimensional features and the face alignment feature set of the reference picture in a temporary database;
and 4, step 4: the processing module maps the input image and maps the texture of the input image to the corresponding position of a reference image;
specifically, a processing module extracts three-dimensional features of an input picture to obtain textures of corresponding positions;
acquiring a corresponding three-dimensional coordinate point set of a reference picture according to a face alignment feature set of an input picture;
and 5: and the processing module assigns the texture acquired from the input picture to the corresponding coordinate in the three-dimensional coordinate point set of the reference picture in an interpolation mode.
Step 6: the processing module fuses the face picture into the reference picture through an alpha channel or Poisson to replace the face in the reference picture.
Claims (2)
1. A face image transformation method based on face three-dimensional reconstruction and face alignment is characterized in that:
the following steps are adopted for the preparation of the anti-cancer medicine,
step 1: the three-dimensional image acquisition device acquires a three-dimensional image of a human face as an input image and transmits the input image to the processing module;
step 2: extracting three-dimensional characteristics of the input image by a face recognition module;
the three-dimensional features of the input image comprise coordinate values of a face feature point set;
storing a standard face alignment feature set in a standard face database, wherein the face alignment feature set is composed of face alignment feature points, and each face alignment feature point is semantic information of a corresponding point on a face;
and step 3: a reference picture database is arranged, and a processing module extracts a reference picture from the reference picture database and transmits the reference picture to a face recognition module;
the face recognition module extracts the three-dimensional features and the face alignment feature set of the reference picture and stores the three-dimensional features and the face alignment feature set of the reference picture in a temporary database;
and 4, step 4: the processing module maps the input image and maps the texture of the input image to the corresponding position of a reference image;
specifically, a processing module extracts three-dimensional features of an input picture to obtain textures of corresponding positions;
acquiring a corresponding three-dimensional coordinate point set of a reference picture according to a face alignment feature set of an input picture;
and 5: the processing module assigns the texture acquired from the input picture to the corresponding coordinate in the three-dimensional coordinate point set of the reference picture in an interpolation mode;
step 6: the processing module fuses the face picture into the reference picture through Poisson and replaces the face in the reference picture.
2. The method for transforming the human face image based on the human face three-dimensional reconstruction and the human face alignment as claimed in claim 1, wherein: and step 6, the processing module fuses the face picture into the reference picture through an alpha channel.
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