CN105608722A - Face key point-based automatic under-eye bag removing method and system - Google Patents

Face key point-based automatic under-eye bag removing method and system Download PDF

Info

Publication number
CN105608722A
CN105608722A CN201510945570.2A CN201510945570A CN105608722A CN 105608722 A CN105608722 A CN 105608722A CN 201510945570 A CN201510945570 A CN 201510945570A CN 105608722 A CN105608722 A CN 105608722A
Authority
CN
China
Prior art keywords
pouch
image
new
area image
channel
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510945570.2A
Other languages
Chinese (zh)
Other versions
CN105608722B (en
Inventor
黄亮
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chengdu Pinguo Technology Co Ltd
Original Assignee
Chengdu Pinguo Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Chengdu Pinguo Technology Co Ltd filed Critical Chengdu Pinguo Technology Co Ltd
Priority to CN201510945570.2A priority Critical patent/CN105608722B/en
Publication of CN105608722A publication Critical patent/CN105608722A/en
Application granted granted Critical
Publication of CN105608722B publication Critical patent/CN105608722B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/40—Filling a planar surface by adding surface attributes, e.g. colour or texture

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Image Processing (AREA)
  • Image Analysis (AREA)

Abstract

The invention belongs to the image processing field and includes a face key point-based automatic under-eye bag removing method and system. The method includes the following steps that: an input image is obtained; the masking-out image and under-eye bag area image of the under-eye bag area of the input image are extracted; the under-eye bag area image is transformed to an LAB color space, and a color channel L, a color channel A and a color channel B are separated out; a brightness adjustment curve is obtained through calculation based on the channel L; the channel L is mapped by the brightness adjustment curve, so that a new channel L is obtained; the new channel L, the channel A and the channel B are converted into an RGB color space image; Gaussian blur is performed on the masking-out image of the under-eye bag area, so that a new masking-out image can be obtained; the under-eye bag area image, the RGB color space image and the new masking-out image are composited, so that a new under-eye bag area image can be obtained; and the under-eye bag area image is replaced by the new under-eye bag area image, so that a final image can be obtained. With the face key point-based automatic under-eye bag removing method and system of the invention adopted, the removal of under-eye bags can be completed through one-key operation. The method is simple and stable, and the effect of an image processed by using the method is natural.

Description

A kind ofly automatically go pouch method and system based on face key point
Technical field
The invention belongs to technical field of image processing, particularly relate to and a kind ofly automatically go to pouch side based on face key pointMethod and system.
Background technology
In recent years, along with scientific and technological progress, the mobile devices such as smart mobile phone, flat board have become the requisite number of peopleWord converter tools. Be accompanied by the rise of smart machine, the demand that U.S. face is autodyned also constantly increases, and wherein goes pouch function to be subject to extensivelyLarge women user pursues.
Conventional method is to adopt the manual mode of clicking screen at present, utilizes finger to click screen appointment and need to remove districtTerritory also highlights operation. This mode in use often can need to re-start pouch because of maloperation and remove behaviourDo, make the process of pouch very complicated, and cannot accurately locate pouch region, have the impact of isolated noise, to formerThe color of figure can cause damage, and makes the image after beautifying seem very unnatural.
Summary of the invention
In order to address the above problem, the present invention propose a kind of based on face key point automatically go pouch method and system,To realize the removal that user can one-key operation pouch, the method simple and stable, and image effect after treatment nature.
For achieving the above object, the technical solution used in the present invention is: a kind ofly automatically remove pouch based on face key pointMethod, described method comprises step:
(1) obtain input picture, described input picture can adopt 3 passage RGB images.
(2) extract masking-out figure and the pouch area image in the pouch region of described input picture.
(3) described pouch area image is transformed into LAB color space, and isolates Color Channel L, passage A and passageB。
(4) calculate brightness adjustment curve by described passage L.
(5) by described brightness adjustment curve, passage L is shone upon, obtain new tunnel L.
(6) new tunnel L, passage A and channel B are converted to rgb color space image.
(7) the masking-out figure in described pouch region is carried out to Gaussian Blur and obtain new masking-out figure.
(8) synthetic described pouch area image, rgb color space image and new masking-out figure, obtain new pouch area image.
(9) new pouch area image is replaced pouch area image, obtains final image.
Further, described step (2) comprises step:
(2.1) described input picture is carried out to face critical point detection, obtain face key point information.
(2.2) key point information of existing standard faces figure and described face key point information are shone upon, obtainMapping matrix.
(2.3) by mapping matrix, external the pouch in standard faces figure quadrilateral area is mapped in input picture,Obtain the illiteracy plate figure in the pouch region in input picture.
(2.4) extract in input picture in the data of covering plate figure corresponding region, as pouch area image.
Further, described face key point information comprises informer's mid point, a left side under the left eye exterior angle, left eye of left face partInformer's mid point, right eye interior angle and right nasal fossa under angulus oculi medialis, left nasal fossa and right eye exterior angle, right eye.
Further, described standard faces figure adopts single channel standard faces figure, described single channel standard faces figure eyeBag region is through demarcating in advance, and being initialized as white and pixel value is 255, and other region is that black pixel value is 0.
Further, described step (4) comprises step:
(4.1) described passage L is carried out to statistics with histogram, obtain statistics.
(4.2) calculate four groups of mappings according to described statistics right.
(4.3) right according to described four groups of mappings, obtain brightness adjustment curve.
Further, described statistics comprises bright pixel value A and dark pixel values B; Described four groups of mappings are to being respectively(L0,H0),(L1,H1),(L2,H2),(L3,H3)。
Wherein, L3=H3=255，L2=H2=A，L1=B，H1=A-0.4142×(A-B)，L0=0,H0=H1–B×(A-H1)/(A-B)。
Further, described step (4.3), comprises step:
(4.3.1) compute matrix H.
, wherein hi=Hi+1-Li,i=0,1,2。
(4.3.2) compute matrix M=[m1,m2]T。
(4.3.3) compute matrix Y.
Y=6×[(H2-H1)/h1-(H1–H0)/h0,(H3–H2)/h2-(H2–H1)/h1]T。
(4.3.4) solving equation H × M=Y, and make m0=m3=0, obtain m1,m2Value.
(4.3.5) calculate the cubic polynomial coefficient a of each segment matched curvei,bi,ci,di。
Wherein, ai=Hi。
bi=(Hi+1-Hi)/hi-hi×mi/2-hi×(mi+1-mi)/6。
ci=mi/2。
di=(mi+1-mi)/(6hi)。
(4.3.6) according to cubic polynomial coefficient ai,bi,ci,di, respectively at interval [Li,Li+1] the upper y value of calculating, specifically publicFormula is:
y=ai+bi×(x-xi)+ci×(x-xi)2+di×(x-xi)3，i=0,1,2。
(4.3.7) be brightness adjustment curve by x to the mapping of y.
Further, in described step (7), described Gaussian Blur carries out convolution by Gauss's template to image, described inConvolution process adopts IIR filtering to be optimized.
Further, in described step (8), utilize composite formula to synthesize new pouch area image.
On the other hand, the present invention also provide a kind of based on face key point automatically go pouch system, comprising:
Image input module: for obtaining input picture.
Extraction module: for calculating and extract masking-out figure and the pouch area image in pouch region of described input picture.
LAB color space conversion module: described pouch area image is transformed into LAB color space, and isolates colorPassage L, passage A and channel B.
Brightness adjustment module: calculate and obtain brightness adjustment curve, and described brightness adjustment curve is reflected passage LPenetrate, obtain new tunnel L.
Rgb color space modular converter: new tunnel L, passage A and channel B are converted to rgb color space image.
Gaussian Blur module: the masking-out figure in described pouch region is carried out to Gaussian Blur and obtain new masking-out figure.
Synthesis module: synthetic described pouch area image, rgb color space image and new masking-out figure, obtain new pouch districtArea image.
Image output module, new pouch area image is replaced pouch area image, obtains final image.
Adopt the beneficial effect of the technical program:
Proposed by the invention a kind of based on face key point automatically go pouch method, by key point, take a mappingThe pouch region that mode obtains is accurate; By generating brightness curve, make the image after brightness adjustment more natural, and can reduceThe impact of isolated noise; By adjusting at LAB color space, reduce the color loss of former figure; One proposed by the inventionBased on face key point automatically go pouch system, can coordinate method proposed by the invention to realize the application of the method.
Brief description of the drawings
Fig. 1 is a kind of flow chart that automatically goes pouch method based on face key point of the present invention;
Fig. 2 is the masking-out figure in pouch region and the method flow of pouch area image that extracts described input picture in the present inventionFigure;
Fig. 3 is the method flow diagram that calculates brightness adjustment curve in the present invention;
Fig. 4 is according to the method flow diagram shining upon calculating brightness adjustment curve in the present invention;
Fig. 5 is a kind of structural representation that automatically goes pouch system based on face key point of the present invention.
Detailed description of the invention
In order to make the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing, the present invention is done into oneStep is set forth.
In the present embodiment, shown in Figure 1, a kind ofly automatically go pouch method, described method based on face key pointComprise step:
(1) obtain input picture, described input picture can adopt 3 passage RGB images.
(2) extract masking-out figure and the pouch area image in the pouch region of described input picture.
As shown in Figure 2, described step (2) comprises step:
(2.1) described input picture is carried out to face critical point detection, obtain face key point information.
Described face key point information comprises informer's mid point, left eye interior angle, left nose under the left eye exterior angle, left eye of left face partInformer's mid point, right eye interior angle and right nasal fossa under ditch and right eye exterior angle, right eye.
(2.2) key point information of existing standard faces figure and described face key point information are shone upon, obtainMapping matrix.
(2.3) by mapping matrix, external the pouch in standard faces figure quadrilateral area is mapped in input picture,Obtain the illiteracy plate figure in the pouch region in input picture.
Described standard faces figure adopts single channel standard faces figure, and described single channel standard faces figure pouch region is through thingFirst demarcate, being initialized as white and pixel value is 255, and other region is that black pixel value is 0.
(2.4) extract in input picture in the data of covering plate figure corresponding region, as pouch area image.
(3) described pouch area image is transformed into LAB color space, and isolates Color Channel L, passage A and passageB。
The concrete grammar of conversion is as follows:
L=0.2126×r+0.7152×g+0.0722×b。
A=1.4749×(0.2213×r-0.3390×g+0.1177×b)+0.5×255。
B=0.6245×(0.1949×r+0.6057×g-0.8006×b)+0.5×255。
Wherein, r, g, b is pixel value in pouch area image, L, A, B is respectively the picture in passage L, passage A and channel BElement value.
(4) calculate brightness adjustment curve by described passage L, as shown in Figure 3, comprise step:
(4.1) described passage L is carried out to statistics with histogram, obtain statistics.
Described statistics comprises bright pixel value A and dark pixel values B; Wherein A is front 30% the brightest partial pixel in passage LAverage, B is the average of front 30% dark-part pixel in passage L.
(4.2) calculate four groups of mappings according to described statistics right.
Described four groups of mappings are to being respectively (L0,H0),(L1,H1),(L2,H2),(L3,H3), for keeping highlights imageValue.
Wherein, L3=H3=255，L2=H2=A，L1=B，H1=A-0.4142×(A-B)，L0=0,H0=H1–B×(A-H1)/(A-B)；(Li,Hi) represent brightness value LiBe mapped as Hi(i=0,1,2,3)。
(4.3) right according to described four groups of mappings, obtain brightness adjustment curve.
As shown in Figure 4, comprise step:
(4.3.1) compute matrix H;
, wherein hi=Hi+1-Li,i=0,1,2；
(4.3.2) compute matrix M=[m1,m2]T；
(4.3.3) compute matrix Y;
Y=6×[(H2-H1)/h1-(H1–H0)/h0,(H3–H2)/h2-(H2–H1)/h1]T；
(4.3.4) solving equation H × M=Y, and make m0=m3=0, obtain m1,m2Value;
(4.3.5) calculate the cubic polynomial coefficient a of each segment matched curvei,bi,ci,di；
Wherein, ai=Hi；
bi=(Hi+1-Hi)/hi-hi×mi/2-hi×(mi+1-mi)/6；
ci=mi/2；
di=(mi+1-mi)/(6hi)；
(4.3.6) according to cubic polynomial coefficient ai,bi,ci,di, respectively at interval [Li,Li+1] the upper y value of calculating, concrete formulaFor:
y=ai+bi×(x-xi)+ci×(x-xi)2+di×(x-xi)3，i=0,1,2；
(4.3.7) be brightness adjustment curve by x to the mapping of y.
(5) by described brightness adjustment curve, passage L is shone upon, obtain new tunnel L.
Described brightness adjustment curve mapping process is that the value on abscissa is mapped to ordinate, with function representation be y=f(x)，x,y∈[0,255]；
Be Channel_L_new (i)=f (Channel_L (i)), Channel_L_new (i) and Channel_L (i) show respectivelyShow the pixel value in new tunnel L and passage L.
(6) new tunnel L, passage A and channel B are converted to rgb color space image.
Conversion method is as follows:
r=L+((A-0.5×255)×0.682353×3.07989502+(B-0.5×255)×0.607843×0.542907715)。
g=L-((A-0.5×255)×0.682353×0.92089844+(B-0.5×255)×0.607843×0.045196535)。
b=L+((A-0.5×255)×0.682353×0.05310059-(B-0.5×255)×0.607843×1.151092529)。
Wherein L, A, B is respectively the value of the pixel in image new tunnel L, passage A and channel B, and r, g, b are rgb color skyBetween the value of pixel in image.
(7) the masking-out figure in described pouch region is carried out to Gaussian Blur and obtain new masking-out figure.
Described Gaussian Blur carries out convolution by Gauss's template to image, and described convolution process adopts IIR filtering to enterRow is optimized.
Gauss's template can be described with following formula:
Convolution process is R_mask_new (i, j)=1/ ∑ w (x, y) * ∑ (w (x, y) * R_mask (i+x, j+y)); X, y ∈ [3 σ, 3 σ], be also the summation scope of ∑.
Wherein, R_mask_new (i, j) is the pixel value of the capable j row of i in new masking-out figure, and R_mask (i+x, j+y) is pouchThe pixel value of the capable j+y row of i+x in the masking-out figure in region, σ gets 10, and in order to accelerate arithmetic speed, convolution process adopts IIR filteringJourney is optimized.
(8) synthetic described pouch area image, rgb color space image and new masking-out figure, obtain new pouch area image.
Utilize composite formula to synthesize new pouch area image.
Composite formula is: (a × alpha+b × (255 – alpha))/255.
Wherein, a is the pixel in described rgb color space image, and b is the pixel in described pouch area image, alphaFor the pixel in new masking-out figure.
(9) new pouch area image is replaced pouch area image, obtains final image.
For coordinating the realization of the inventive method, based on identical inventive concept, shown in Figure 5, the present invention also providesBased on face key point automatically go a pouch system, comprising:
Image input module: for obtaining input picture.
Extraction module: for calculating and extract masking-out figure and the pouch area image in pouch region of described input picture.
LAB color space conversion module: described pouch area image is transformed into LAB color space, and isolates colorPassage L, passage A and channel B.
Brightness adjustment module: calculate and obtain brightness adjustment curve, and described brightness adjustment curve is reflected passage LPenetrate, obtain new tunnel L.
Rgb color space modular converter: new tunnel L, passage A and channel B are converted to rgb color space image.
Gaussian Blur module: the masking-out figure in described pouch region is carried out to Gaussian Blur and obtain new masking-out figure.
Synthesis module: synthetic described pouch area image, rgb color space image and new masking-out figure, obtain new pouch districtArea image.
Image output module, new pouch area image is replaced pouch area image, obtains final image.
More than show and described general principle of the present invention and principal character and advantage of the present invention. The technology of the industryPersonnel should understand, and the present invention is not restricted to the described embodiments, and the just explanation of describing in above-described embodiment and description originallyThe principle of invention, without departing from the spirit and scope of the present invention, the present invention also has various changes and modifications, these changesChange and improve and all fall in the claimed scope of the invention. The claimed scope of this reality invention by appending claims andIts equivalent defines.

Claims (10)

  1. Based on face key point automatically go a pouch method, it is characterized in that, described method comprises step:
    (1) obtain input picture;
    (2) extract masking-out figure and the pouch area image in the pouch region of described input picture;
    (3) described pouch area image is transformed into LAB color space, and isolates Color Channel L, passage A and channel B;
    (4) calculate brightness adjustment curve by described passage L;
    (5) by described brightness adjustment curve, passage L is shone upon, obtain new tunnel L;
    (6) new tunnel L, passage A and channel B are converted to rgb color space image;
    (7) the masking-out figure in described pouch region is carried out to Gaussian Blur and obtain new masking-out figure;
    (8) synthetic described pouch area image, rgb color space image and new masking-out figure, obtain new pouch area image;
    (9) new pouch area image is replaced pouch area image, obtains final image.
  2. 2. according to claim 1ly a kind ofly automatically go pouch method, its feature of described step (2) based on face key pointBe, comprise step:
    Described input picture is carried out to face critical point detection, obtain face key point information;
    The key point information of existing standard faces figure and described face key point information are shone upon, obtain mapping matrix;
    By mapping matrix, external the pouch in standard faces figure quadrilateral area is mapped in input picture, inputtedThe illiteracy plate figure in the pouch region in image;
    Extract in input picture in the data of covering plate figure corresponding region, as pouch area image.
  3. According to claim 2 a kind of based on face key point automatically go pouch method, it is characterized in that described peopleFace key point information comprises under the left eye exterior angle, left eye of left face part outside informer's mid point, left eye interior angle, left nasal fossa and right eyeInformer's mid point, right eye interior angle and right nasal fossa under angle, right eye.
  4. According to claim 3 a kind of based on face key point automatically go pouch method, it is characterized in that described markAccurate face figure adopts single channel standard faces figure, and described single channel standard faces figure pouch region, through demarcating in advance, initializesFor white and pixel value are 255, other region is that black pixel value is 0.
  5. 5. according to claim 1ly a kind ofly automatically go pouch method, its feature of described step (4) based on face key pointBe, comprise step:
    Described passage L is carried out to statistics with histogram, obtain statistics;
    Calculate four groups of mappings according to described statistics right;
    Right according to described four groups of mappings, obtain brightness adjustment curve.
  6. According to claim 5 a kind of based on face key point automatically go pouch method, it is characterized in that described systemCount and comprise bright pixel value A and dark pixel values B; Described four groups of mappings are to being respectively (L0,H0),(L1,H1),(L2,H2),(L3,H3)；
    Wherein, L3=H3=255，L2=H2=A，L1=B，H1=A-0.4142×(A-B)，L0=0,H0=H1–B×(A-H1)/(A-B)。
  7. 7. according to claim 6ly a kind ofly automatically go pouch method, its spy of described step (4.3) based on face key pointLevy and be, comprise step: compute matrix H;
    , wherein hi=Hi+1-Li,i=0,1,2；
    Compute matrix M=[m1,m2]T；
    Compute matrix Y;
    Y=6×[(H2-H1)/h1-(H1–H0)/h0,(H3–H2)/h2-(H2–H1)/h1]T；
    Solving equation H × M=Y, and make m0=m3=0, obtain m1,m2Value;
    Calculate the cubic polynomial coefficient a of each segment matched curvei,bi,ci,di；
    Wherein, ai=Hi；
    bi=(Hi+1-Hi)/hi-hi×mi/2-hi×(mi+1-mi)/6；
    ci=mi/2；
    di=(mi+1-mi)/(6hi)；
    According to cubic polynomial coefficient ai,bi,ci,di, respectively at interval [Li,Li+1] the upper y value of calculating, concrete formula is:
    y=ai+bi×(x-xi)+ci×(x-xi)2+di×(x-xi)3，i=0,1,2；
    Be brightness adjustment curve by x to the mapping of y.
  8. 8. according to claim 1ly a kind ofly automatically go pouch method, its feature of described step (7) based on face key pointBe, described Gaussian Blur carries out convolution by Gauss's template to image, and described convolution process adopts IIR filtering to carry out excellentChange.
  9. 9. according to claim 1ly a kind ofly automatically go pouch method, its feature of described step (8) based on face key pointBe, utilize composite formula to synthesize new pouch area image.
  10. Based on face key point automatically go a pouch system, it is characterized in that, comprise,
    Image input module: for obtaining input picture;
    Extraction module: for calculating and extract masking-out figure and the pouch area image in pouch region of described input picture;
    LAB color space conversion module: described pouch area image is transformed into LAB color space, and isolates Color ChannelL, passage A and channel B;
    Brightness adjustment module: calculate and obtain brightness adjustment curve, and described brightness adjustment curve is shone upon passage L,Obtain new tunnel L;
    Rgb color space modular converter: new tunnel L, passage A and channel B are converted to rgb color space image;
    Gaussian Blur module: the masking-out figure in described pouch region is carried out to Gaussian Blur and obtain new masking-out figure;
    Synthesis module: synthetic described pouch area image, rgb color space image and new masking-out figure, obtain new pouch administrative division mapPicture;
    Image output module, new pouch area image is replaced pouch area image, obtains final image.
CN201510945570.2A 2015-12-17 2015-12-17 It is a kind of that pouch method and system are gone based on face key point automatically Active CN105608722B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510945570.2A CN105608722B (en) 2015-12-17 2015-12-17 It is a kind of that pouch method and system are gone based on face key point automatically

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510945570.2A CN105608722B (en) 2015-12-17 2015-12-17 It is a kind of that pouch method and system are gone based on face key point automatically

Publications (2)

Publication Number Publication Date
CN105608722A true CN105608722A (en) 2016-05-25
CN105608722B CN105608722B (en) 2018-08-31

Family

ID=55988637

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510945570.2A Active CN105608722B (en) 2015-12-17 2015-12-17 It is a kind of that pouch method and system are gone based on face key point automatically

Country Status (1)

Country Link
CN (1) CN105608722B (en)

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107424115A (en) * 2017-05-31 2017-12-01 成都品果科技有限公司 A kind of colour of skin correction algorithm based on face key point
CN107578393A (en) * 2017-09-26 2018-01-12 成都国翼电子技术有限公司 A kind of Aerial Images brightness adjusting method based on man-machine interactively
CN107633492A (en) * 2017-09-26 2018-01-26 成都国翼电子技术有限公司 A kind of shadow of object fast positioning and the method removed
CN107644407A (en) * 2017-09-26 2018-01-30 成都国翼电子技术有限公司 A kind of thin cloud minimizing technology of Aerial Images based on man-machine interactively
CN107657596A (en) * 2017-09-26 2018-02-02 成都国翼电子技术有限公司 A kind of Aerial Images color adjustment method based on man-machine interactively
CN107680055A (en) * 2017-09-26 2018-02-09 成都国翼电子技术有限公司 A kind of Aerial Images haze minimizing technology based on man-machine interactively
CN107862673A (en) * 2017-10-31 2018-03-30 北京小米移动软件有限公司 Image processing method and device
CN108898546A (en) * 2018-06-15 2018-11-27 北京小米移动软件有限公司 Face image processing process, device and equipment, readable storage medium storing program for executing
CN109639958A (en) * 2017-10-05 2019-04-16 卡西欧计算机株式会社 Image processing apparatus, image processing method and recording medium
CN109919030A (en) * 2019-01-31 2019-06-21 深圳和而泰数据资源与云技术有限公司 Black eye kind identification method, device, computer equipment and storage medium
CN110288512A (en) * 2019-05-16 2019-09-27 成都品果科技有限公司 Illumination for image synthesis remaps method, apparatus, storage medium and processor
CN110363717A (en) * 2019-06-28 2019-10-22 北京字节跳动网络技术有限公司 A kind of method, apparatus, medium and electronic equipment handling face-image
CN111784604A (en) * 2020-06-29 2020-10-16 北京字节跳动网络技术有限公司 Image processing method, device, equipment and computer readable storage medium
CN111882627A (en) * 2020-07-20 2020-11-03 广州市百果园信息技术有限公司 Image processing method, video processing method, device, equipment and storage medium
CN113298698A (en) * 2021-04-30 2021-08-24 成都东方盛行电子有限责任公司 Pouch removing method for key points of human face in non-woven engineering

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103914699A (en) * 2014-04-17 2014-07-09 厦门美图网科技有限公司 Automatic lip gloss image enhancement method based on color space
CN104537630A (en) * 2015-01-22 2015-04-22 厦门美图之家科技有限公司 Method and device for image beautifying based on age estimation
CN104574285A (en) * 2013-10-23 2015-04-29 厦门美图网科技有限公司 Method for automatically removing image black eyes
US20150302564A1 (en) * 2014-04-16 2015-10-22 Etron Technology, Inc. Method for making up a skin tone of a human body in an image, device for making up a skin tone of a human body in an image, method for adjusting a skin tone luminance of a human body in an image, and device for adjusting a skin tone luminance of a human body in an image
CN105096243A (en) * 2015-09-10 2015-11-25 成都品果科技有限公司 Method and system for achieving makeup effect by LM algorithm

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104574285A (en) * 2013-10-23 2015-04-29 厦门美图网科技有限公司 Method for automatically removing image black eyes
US20150302564A1 (en) * 2014-04-16 2015-10-22 Etron Technology, Inc. Method for making up a skin tone of a human body in an image, device for making up a skin tone of a human body in an image, method for adjusting a skin tone luminance of a human body in an image, and device for adjusting a skin tone luminance of a human body in an image
CN103914699A (en) * 2014-04-17 2014-07-09 厦门美图网科技有限公司 Automatic lip gloss image enhancement method based on color space
CN104537630A (en) * 2015-01-22 2015-04-22 厦门美图之家科技有限公司 Method and device for image beautifying based on age estimation
CN105096243A (en) * 2015-09-10 2015-11-25 成都品果科技有限公司 Method and system for achieving makeup effect by LM algorithm

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
宋阳 等: "基于照片的可编辑光照效果卡通人脸生成算法", 《图学学报》 *
戴勇 等: "人脸图像中斑点自动去除***的设计与实现", 《宁波工程学院学报》 *
王章野 等: "基于个性化原型的人脸衰老图像合成", 《电子学报》 *

Cited By (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107424115A (en) * 2017-05-31 2017-12-01 成都品果科技有限公司 A kind of colour of skin correction algorithm based on face key point
CN107578393A (en) * 2017-09-26 2018-01-12 成都国翼电子技术有限公司 A kind of Aerial Images brightness adjusting method based on man-machine interactively
CN107633492A (en) * 2017-09-26 2018-01-26 成都国翼电子技术有限公司 A kind of shadow of object fast positioning and the method removed
CN107644407A (en) * 2017-09-26 2018-01-30 成都国翼电子技术有限公司 A kind of thin cloud minimizing technology of Aerial Images based on man-machine interactively
CN107657596A (en) * 2017-09-26 2018-02-02 成都国翼电子技术有限公司 A kind of Aerial Images color adjustment method based on man-machine interactively
CN107680055A (en) * 2017-09-26 2018-02-09 成都国翼电子技术有限公司 A kind of Aerial Images haze minimizing technology based on man-machine interactively
CN107578393B (en) * 2017-09-26 2021-12-10 成都国翼电子技术有限公司 Aerial image brightness adjusting method based on manual interaction
CN109639958A (en) * 2017-10-05 2019-04-16 卡西欧计算机株式会社 Image processing apparatus, image processing method and recording medium
CN107862673A (en) * 2017-10-31 2018-03-30 北京小米移动软件有限公司 Image processing method and device
CN107862673B (en) * 2017-10-31 2021-08-24 北京小米移动软件有限公司 Image processing method and device
CN108898546A (en) * 2018-06-15 2018-11-27 北京小米移动软件有限公司 Face image processing process, device and equipment, readable storage medium storing program for executing
CN108898546B (en) * 2018-06-15 2022-08-16 北京小米移动软件有限公司 Face image processing method, device and equipment and readable storage medium
CN109919030A (en) * 2019-01-31 2019-06-21 深圳和而泰数据资源与云技术有限公司 Black eye kind identification method, device, computer equipment and storage medium
CN110288512A (en) * 2019-05-16 2019-09-27 成都品果科技有限公司 Illumination for image synthesis remaps method, apparatus, storage medium and processor
CN110363717B (en) * 2019-06-28 2021-07-23 北京字节跳动网络技术有限公司 Method, device, medium and electronic equipment for processing face image
CN110363717A (en) * 2019-06-28 2019-10-22 北京字节跳动网络技术有限公司 A kind of method, apparatus, medium and electronic equipment handling face-image
CN111784604A (en) * 2020-06-29 2020-10-16 北京字节跳动网络技术有限公司 Image processing method, device, equipment and computer readable storage medium
CN111882627A (en) * 2020-07-20 2020-11-03 广州市百果园信息技术有限公司 Image processing method, video processing method, device, equipment and storage medium
CN113298698A (en) * 2021-04-30 2021-08-24 成都东方盛行电子有限责任公司 Pouch removing method for key points of human face in non-woven engineering
CN113298698B (en) * 2021-04-30 2024-02-02 成都东方盛行电子有限责任公司 Pouch removing method for face key points in non-woven engineering

Also Published As

Publication number Publication date
CN105608722B (en) 2018-08-31

Similar Documents

Publication Publication Date Title
CN105608722A (en) Face key point-based automatic under-eye bag removing method and system
CN104200470B (en) Blue screen image-matting method
CN106331850B (en) Browser live broadcast client, browser live broadcast system and browser live broadcast method
US10846836B2 (en) View synthesis using deep convolutional neural networks
CN103927016B (en) Real-time three-dimensional double-hand gesture recognition method and system based on binocular vision
US11467661B2 (en) Gaze-point determining method, contrast adjusting method, and contrast adjusting apparatus, virtual reality device and storage medium
US20180204052A1 (en) A method and apparatus for human face image processing
WO2016101883A1 (en) Method for face beautification in real-time video and electronic equipment
WO2019024751A1 (en) Facial expression synthesis method and apparatus, electronic device, and storage medium
CN110322468A (en) A kind of automatic edit methods of image
EP3067862A2 (en) Image processing method and apparatus
CN108388882A (en) Based on the gesture identification method that the overall situation-part is multi-modal RGB-D
CN109525786B (en) Video processing method and device, terminal equipment and storage medium
CN106169078B (en) Image-recognizing method
US8488899B2 (en) Image processing apparatus, method and recording medium
CN106937059A (en) Image synthesis method and system based on Kinect
CN107220955A (en) A kind of brightness of image equalization methods based on overlapping region characteristic point pair
CN105791636A (en) Video processing system
CN105913400A (en) Device for obtaining high-quality and real-time beautiful image
CN104200427A (en) Method for eliminating edge sawteeth of images
CN106909871A (en) Gesture instruction recognition methods
CN105976309A (en) High-efficiency and easy-parallel implementation beauty mobile terminal
CN104732497A (en) Image defogging method, FPGA and defogging system including FPGA
CN104240259A (en) High-speed photographing instrument voucher intelligent edge cutting and correcting system and high-speed photographing instrument voucher intelligent edge cutting and correcting method based on silhouette extraction
CN103455974B (en) Image sketching style processing method

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CP02 Change in the address of a patent holder
CP02 Change in the address of a patent holder

Address after: 610041 the 13 floor of No. 1 middle Tianfu Avenue, No. 1268, high-tech zone, Chengdu, Sichuan.

Patentee after: Chengdu PinGuo Digital Entertainment Ltd.

Address before: 3, 13 floor, E zone, Tianfu Software Park, Chengdu hi tech Zone, Sichuan, 610000

Patentee before: Chengdu PinGuo Digital Entertainment Ltd.

CB03 Change of inventor or designer information
CB03 Change of inventor or designer information

Inventor after: Huang Liang

Inventor after: Xu Hao

Inventor after: Xu Ying

Inventor after: Yang Jia

Inventor before: Huang Liang