Face exchange method

A facial feature and 3D technology, applied in the field of face exchange, can solve problems such as unrealistic and inability to guarantee similarity

Pending Publication Date: 2020-01-07
北京紫睛科技有限公司 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] (3) Deep learning is often used to deal with face transformation, just like style transformation between images. This method may require training a separate network for each source image, which is impractical for most applications

Method used

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Embodiment Construction

[0043] The present invention uses a standard segmentation network obtained through rich and diverse sample training to achieve accurate and fast segmentation of the human face from the background and occlusion. Without any constraints on the image, the face exchange is more realistic and makes the human face more realistic. Changes in face and reduction in recognition rate; the present invention will be described in detail below in conjunction with specific embodiments and accompanying drawings.

[0044] like figure 1 As shown, the present invention provides a kind of face exchange method, comprises the following steps:

[0045] S1, input source image I S and the target image I T , use the detector to get facial landmarks.

[0046] First locate the facial feature points of each image. This embodiment uses a ready-made detector to achieve this purpose. Dlib implements the core algorithm of the detector. The algorithm itself is very complicated, and the effect of extracting f...

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Abstract

The invention discloses a face exchange method, which comprises the following steps of: inputting a source image and a target image, and acquiring face feature points by using a detector; adjusting the shape of the 3D face through the obtained face feature points; performing face segmentation on the adjusted 3D face shape by adopting an FCN detection model after sample training, and segmenting faces in the source image and the target image from background and occlusion; the face of the target image is effectively covered with the face of the source image, and fusion is carried out; and outputting the picture after face exchange. According to the method, a standard segmentation network obtained by training on rich and diverse samples is used; the FCN realizes accurate and rapid segmentationof the face from the background and the occlusion, and efficiently processes face alignment, face segmentation, 3D shape estimation, expression estimation and the like without any constraint on the image, so that face exchange is more real, and the face change and the recognition rate are reduced.

Description

technical field [0001] The invention relates to the technical field of face detection, in particular to a face exchange method. Background technique [0002] Face swapping was realized as a fully automatic technology more than ten years ago. Its original purpose was to respond to privacy protection issues: it is used to process photos that can be seen everywhere in the public network environment. Face swapping can make the characters appearing in it Features become obscured as a substitute. Since then, however, many face-swapping applications have come more from pastime or entertainment. [0003] Most of the existing face-changing systems have several key aspects in common. [0004] (1) Many methods limit the target photos used for conversion. Given a source image, select a target image that is relatively easier for face exchange from a large face set, such as the target image and the source image. Appearance, including facial tone, posture, expression, etc. Although the...

Claims

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Application Information

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IPC IPC(8): G06T7/194G06T5/50G06T3/00G06K9/00
CPCG06T7/194G06T5/50G06T3/0068G06T2207/10012G06T2207/20221G06T2207/20081G06T2207/20084G06T2207/30201G06V40/174G06V40/168
Inventor 周继乐储超群唐江平
Owner 北京紫睛科技有限公司
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