CN109509142A - A kind of face ageing image processing method, system, readable storage medium storing program for executing and equipment - Google Patents
A kind of face ageing image processing method, system, readable storage medium storing program for executing and equipment Download PDFInfo
- Publication number
- CN109509142A CN109509142A CN201811268768.1A CN201811268768A CN109509142A CN 109509142 A CN109509142 A CN 109509142A CN 201811268768 A CN201811268768 A CN 201811268768A CN 109509142 A CN109509142 A CN 109509142A
- Authority
- CN
- China
- Prior art keywords
- face
- picture
- ageing
- target
- module
- 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.)
- Pending
Links
- 230000032683 aging Effects 0.000 title claims abstract description 72
- 238000003672 processing method Methods 0.000 title claims abstract description 28
- 238000003860 storage Methods 0.000 title claims description 9
- 238000012545 processing Methods 0.000 claims abstract description 22
- 238000000605 extraction Methods 0.000 claims abstract description 19
- 239000000284 extract Substances 0.000 claims abstract description 4
- 206010040954 Skin wrinkling Diseases 0.000 claims description 23
- 230000037303 wrinkles Effects 0.000 claims description 21
- 238000001514 detection method Methods 0.000 claims description 16
- 238000010606 normalization Methods 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 12
- 239000000463 material Substances 0.000 claims description 6
- 230000005055 memory storage Effects 0.000 claims description 3
- 238000000034 method Methods 0.000 abstract description 7
- 238000004458 analytical method Methods 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 5
- 238000013528 artificial neural network Methods 0.000 description 4
- 238000012937 correction Methods 0.000 description 3
- 208000032839 leukemia Diseases 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 239000013589 supplement Substances 0.000 description 3
- 241000949648 Angulus Species 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000001815 facial effect Effects 0.000 description 2
- 230000002068 genetic effect Effects 0.000 description 2
- 230000009897 systematic effect Effects 0.000 description 2
- 238000006424 Flood reaction Methods 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000011840 criminal investigation Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 230000029052 metamorphosis Effects 0.000 description 1
- 210000000216 zygoma Anatomy 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/04—Context-preserving transformations, e.g. by using an importance map
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
- G06V40/171—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Oral & Maxillofacial Surgery (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Human Computer Interaction (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Processing Or Creating Images (AREA)
- Collating Specific Patterns (AREA)
Abstract
The present invention provides a kind of face ageing image processing method, method includes the following steps: obtaining target face picture；Feature extraction is carried out to the target face picture and obtains feature vector；Described eigenvector is sorted out in different face dimensions, the face dimension includes at least age, gender, region/race；It obtains the corresponding parent's face picture of the target face picture and extracts the face of parent；Sorted out according to the face of the parent, face dimension and knowledge base carries out ageing processing to target face picture.A kind of face ageing image processing method of the present invention, the estimated informations such as gender, age, race are obtained by analysis face picture first, and estimated information can be supplemented and corrected by input parent's picture, typing additional information, the knowledge base obtained according to face statistical data is finally combined, ageing processing is carried out to face picture.
Description
Technical field
The invention belongs to computer vision fields, and in particular to a kind of face ageing image processing method, readable is deposited at system
Storage media and equipment.
Background technique
As camera hardware module and camera software are in the universal of mobile terminal, taking pictures, it is instantly most fiery to be processed into picture
One of public hobby, and it is that numerous U.S. face APP is applied that various face image processing technologies, which also walk out incarnation from laboratory,
In just include face ageing technology.
Ageing is the reality that everyone will face.Using face ageing technology, people can be allowed to shift to an earlier date according to present
Face appearance foresees following appearance in advance.The technology can also mention other than the curiosity for being able to satisfy people for criminal investigation
For important references.
But present face ageing technology has following limitation:
1. gender differences
It is all being uniformly processed of doing that the appearances of male and female, which changes variant but present face ageing technology, because
And bring error.
2. area differentiation
Due to leading to the difference of facial appearance in the isolation in historical floods between different zones, different nationalities, such as:
The ose breadth of Han nationality is less than Leukemia in Southern Chinese Hans people, and the width of mouth is also less than southerner；The cheekbone of people from Tibetan is generally higher.
And present face ageing technology does not consider this point.
3. hereditary difference
Determine that the most important factor of face appearance is exactly the appearance of parent, and there is no consider for present face ageing technology
To this point.
Summary of the invention
In view of the foregoing deficiencies of prior art, it is an object of the invention to a kind of face ageing image processing method,
System, readable storage medium storing program for executing and equipment.
In order to achieve the above objects and other related objects, the present invention provides a kind of face ageing image processing method, described
Face ageing image processing method include at least:
Obtain target face picture；
Feature extraction is carried out to the target face picture and obtains feature vector；
Described eigenvector is sorted out in different face dimensions, the face dimension includes at least age, property
Not, region/race；
It obtains the corresponding parent's face picture of the target face picture and extracts the face of parent；
Sorted out according to the face of the parent, face dimension and knowledge base carries out ageing processing to target face picture.
Optionally, the acquisition Target Photo, comprising:
Acquire face picture；
Face datection is carried out to obtain human face region to be checked to the face picture；
Calculate the face quality point of face picture；
The face quality point is compared with face quality point threshold value, if the face quality point is in the face quality
Divide in threshold range, then the corresponding face picture of the face quality point is qualified picture；
Face critical point detection is carried out to the human face region to be checked；
Face normalization is carried out to obtain target face picture to face according to face key point.
Optionally, the face dimension further includes personality, ancestral home, father's face picture, mother's face picture.
Optionally, described that target face picture is carried out according to the face of the parent, the classification of face dimension and knowledge base
Ageing processing, specifically includes:
Sorted out according to face dimension and knowledge base carries out first time adjustment to the face of target face picture；
Second is carried out to target face picture according to the face of parent to adjust；
It will be sorted out by face dimension and knowledge base selects the wrinkle texture in material database to be transferred to by second of adjustment
Target face picture afterwards；
Wrinkle color and face color are adjusted, are adapted wrinkle color with face color.
In order to achieve the above objects and other related objects, the present invention also provides a kind of face ageing image processing system, institutes
The face ageing image processing system stated includes at least:
Target face picture acquisition module, for obtaining target face picture；
Characteristic extracting module obtains feature vector for carrying out feature extraction to the target face picture；
Face classifying module, for described eigenvector to be sorted out in different face dimensions, the face dimension
Degree includes at least age, gender, region/race；
Face extraction module, for obtaining the corresponding parent's face picture of the target face picture and extracting parent's
Face；
Face ageing module, for being sorted out according to the face of the parent, face dimension and knowledge base is to target face figure
Piece carries out ageing processing.
Optionally, the target face picture acquisition module to including: less
Acquisition module, for acquiring face picture；
Face detection module, for carrying out Face datection to the face picture to obtain human face region to be checked；
Face quality divides computing module, for calculating the face quality point of face picture；
Comparison module, for the face quality point to be compared with face quality point threshold value, if the face quality point
Divide in threshold range in the face quality, then the corresponding face picture of the face quality point is qualified picture；
Critical point detection module, for carrying out face critical point detection to the human face region to be checked；
Face normalization module carries out face normalization to face according to face key point to obtain target face picture.
Optionally, the face dimension further includes personality, ancestral home, father's face picture, mother's face picture.
Optionally, the face ageing module includes at least:
The first adjustment module carries out first with face of the knowledge base to target face picture for sorting out according to face dimension
Secondary adjustment；
Second adjustment module carries out second to target face picture according to the face of parent and adjusts；
Wrinkle treatment module selects the wrinkle texture in material database to shift for that will sort out by face dimension with knowledge base
To by second of target face picture adjusted；
Third, which adjusts module, makes wrinkle color and face color phase for wrinkle color and face color to be adjusted
Adaptation.
In order to achieve the above objects and other related objects, the present invention also provides a kind of computer readable storage medium, storages
Computer program executes the face ageing image processing method when computer program is run by processor.
In order to achieve the above objects and other related objects, the present invention also provides a kind of equipment, comprising:
Memory, for storing computer program；
Processor, for executing the computer program of the memory storage, so that the equipment executes the face
Ageing image processing method.
As described above, a kind of face ageing image processing method, system, readable storage medium storing program for executing and equipment of the invention, tool
Have following
The utility model has the advantages that
A kind of face ageing image processing method of the present invention and system are obtained by analysis face picture first
The estimated informations such as gender, age, race, and can by the additional information of input parent's picture, typing come to estimated information into
Row supplement and correction, finally combine the knowledge base obtained according to face statistical data, carry out ageing processing to face picture.
Detailed description of the invention
Fig. 1 is a kind of flow chart of face ageing image processing method of the present invention；
Fig. 2 is the method flow diagram for obtaining target face picture；
Fig. 3 is to carry out ageing place to target face picture according to the face of the parent, the classification of face dimension and knowledge base
Manage method flow diagram；
Fig. 4 is a kind of implementation figure of face key point；
Fig. 5 is angle definition figure of the face relative to camera coordinates system；
Fig. 6 is a kind of block diagram of face ageing image processing system of the present invention；
Fig. 7 is the block diagram of target face picture acquisition module；
Fig. 8 is the block diagram of face ageing module.
Specific embodiment
Embodiments of the present invention are illustrated by particular specific embodiment below, those skilled in the art can be by this explanation
Content disclosed by book is understood other advantages and efficacy of the present invention easily.
Illustrate embodiments of the present invention below by way of specific specific example, those skilled in the art can be by this specification
Other advantages and efficacy of the present invention can be easily understood for disclosed content.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints and application, without departing from
Various modifications or alterations are carried out under spirit of the invention.It should be noted that in the absence of conflict, following embodiment and implementation
Feature in example can be combined with each other.
It should be noted that illustrating the basic structure that only the invention is illustrated in a schematic way provided in following embodiment
Think, only shown in schema then with related component in the present invention rather than component count, shape and size when according to actual implementation
Draw, when actual implementation kenel, quantity and the ratio of each component can arbitrarily change for one kind, and its assembly layout kenel
It is likely more complexity.
As shown in Figure 1, the present invention provides a kind of face ageing image processing method, the face ageing image processing method
Method includes at least:
S1 obtains target face picture；
In an embodiment, the acquisition Target Photo, comprising:
As shown in Fig. 2, S11 acquires face picture；
The face picture can be by taking pictures, selecting the modes such as local picture, input image link address to obtain.
S12 carries out Face datection to the face picture to obtain human face region to be checked.
S13 calculates the face quality point of face picture；
In an embodiment, the face quality point can be calculated by Face datection algorithm and be obtained, wherein Face datection
Algorithm includes but is not limited to deep neural network algorithm, stencil matching algorithm.
The face quality point is compared by S14 with face quality point threshold value, if the face quality point is in the face
Quality is divided in threshold range, then the corresponding face picture of the face quality point is qualified picture.
In an embodiment, face quality point is in the valued space of [0,1], and value is bigger, and the face quality that represents is better,
Generic face quality point threshold value is set as 0.8,0.8 with worthwhile excellent.Face quality point threshold value includes but is not limited to be set in advance
Fixed threshold and combine history quality point calculated dynamic threshold.
S15 carries out face critical point detection to the human face region to be checked；
S16 carries out face normalization to face according to face key point to obtain target face picture.
In an embodiment, face normalization is corrected by face normalization algorithm, with compensation because of shooting angle bring
Facial metamorphosis.
A kind of implementation is as follows in face normalization algorithm base:
Using face critical point detection algorithm, the face key point of outlet, nose, mouth, one of which as shown in Figure 3 are detected
Key point definition calculates pitch angle (pitch), the roll of the face of current shooting according to the actual coordinate relationship of these points
Angle (roll), yaw angle (yaw).Wherein the pitch angle of face, roll angle, yaw angle are relative to depending on camera coordinates system
Justice, as shown in Figure 4.
S2 carries out feature extraction to the target face picture and obtains feature vector；
In an embodiment, the extraction of feature vector is realized by face characteristic extraction algorithm, face characteristic extraction algorithm
Including but not limited to deep neural network algorithm, stencil matching algorithm.
S3 sorts out described eigenvector in different face dimensions, the face dimension include at least the age,
Gender, region/race；
Subsumption algorithm includes but is not limited to svm classifier, K-means algorithm.
S4 obtains the corresponding parent's face picture of the target face picture and extracts the face of parent；
The method that the extraction of parent's face picture is referred to target face picture acquisition.
S5 sorts out according to the face of the parent, face dimension and knowledge base carries out ageing processing to target face picture.
In an embodiment, the face according to the parent, face dimension sort out and knowledge base is to target face figure
Piece carries out ageing processing, specifically includes, as shown in Figure 5.
S51 sorts out according to face dimension and knowledge base carries out first time adjustment to the face of target face picture.
It specifically, should according to knowledge base if the target face picture is Leukemia in Southern Chinese Hans people and the age is 30 years old
Face two angulus oculi medialis distances at 60 years old are likely to reduce 1.0mm.
S52 carries out second to target face picture according to the face of parent and adjusts.The purpose of second adjustment be in order to
Meet genetic development.
S53 will be sorted out by face dimension and knowledge base selects the wrinkle texture in material database to be transferred to by second of tune
Target face picture after whole.Specifically, for women, deeper eye pouch is generally had after 50 years old, if user inputs
Personality feature when being " active love laugh at ", then the user generally has smiling face and crow's feet after 40 years old.
Wrinkle color and face color are adjusted by S54, are adapted wrinkle color with face color.
Final output be user different age group afterwards face picture.
In an embodiment, face ageing image processing method further includes customized adjusting judgment step, can be by defeated
Enter other information face ageing to be further processed.
When user other than inputting face picture without providing other information when, then only with from analyzing in face picture
The foundation that the information arrived is handled as subsequent face ageing；When user has input other information, then system can also further divide
It analyses these information and system is corrected.
The other information that user can input include but is not limited to father's face picture, mother's face picture, the age, race,
Ancestral home, personality feature.
It, be according to father's face picture, mother's face picture, age, race, ancestral after user has input other information
Face dimension obtained in nationality, personality feature information, supplement and correction step S3 is sorted out.
The present invention reduces ageing processing by combining the additional informations such as sex, race, parent's human face photo, personality
Error；On the other hand, the present invention also has the characteristics that convenience, including the additional informations such as parent's human face photo and personality be all can
Information is selected, these optional informations can be further reduced systematic error, but even if lacking part of optional information, the present invention is real
Existing precision has also exceeded traditional face ageing system.
As shown in fig. 6, the present invention also provides a kind of face ageing image processing system, the face ageing image procossing
System includes at least target face picture acquisition module 1, characteristic extracting module 2, face classifying module 3,4 and of face extraction module
Face ageing module 5.
The target face picture acquisition module, for obtaining target face picture；
In an embodiment, as shown in fig. 7, the target face picture acquisition module includes at least acquisition module 11, people
Face detection module 12, face quality divide computing module 13, comparison module 14, critical point detection module 15 and face normalization module
16。
The acquisition module, for acquiring face picture.The face picture can by take pictures, select local picture,
The modes such as input image link address obtain.
The face detection module, for carrying out Face datection to the face picture to obtain human face region to be checked；
The face quality divides computing module, for calculating the face quality point of face picture；
In an embodiment, the face quality point can be calculated by Face datection algorithm and be obtained, wherein Face datection
Algorithm includes but is not limited to deep neural network algorithm, stencil matching algorithm.
The comparison module, for the face quality point to be compared with face quality point threshold value, if the face matter
Amount point is divided in threshold range in the face quality, then the corresponding face picture of the face quality point is qualified picture；
In an embodiment, face quality point is in the valued space of [0,1], and value is bigger, and the face quality that represents is better,
Generic face quality point threshold value is set as 0.8,0.8 with worthwhile excellent.Face quality point threshold value includes but is not limited to be set in advance
Fixed threshold and combine history quality point calculated dynamic threshold.
The critical point detection module, for carrying out face critical point detection to the human face region to be checked；
The face normalization module carries out face normalization to face according to face key point to obtain target face picture.
A kind of implementation is as follows in face normalization algorithm base:
Using face critical point detection algorithm, the face key point of outlet, nose, mouth, one of which as shown in Figure 3 are detected
Key point definition calculates pitch angle (pitch), the roll of the face of current shooting according to the actual coordinate relationship of these points
Angle (roll), yaw angle (yaw).Wherein the pitch angle of face, roll angle, yaw angle are relative to depending on camera coordinates system
Justice, as shown in Figure 4.
The characteristic extracting module obtains feature vector for carrying out feature extraction to the target face picture；
In an embodiment, the extraction of feature vector is realized by face characteristic extraction algorithm, face characteristic extraction algorithm
Including but not limited to deep neural network algorithm, stencil matching algorithm.
The face classifying module, for described eigenvector to be sorted out in different face dimensions, the people
Face dimension includes at least age, gender, region/race；
Subsumption algorithm includes but is not limited to svm classifier, K-means algorithm.
The face extraction module, for obtaining the corresponding parent's face picture of the target face picture and extracting father
Female face；The method that the extraction of parent's face picture is referred to target face picture acquisition.
The face ageing module, for being sorted out according to the face of the parent, face dimension and knowledge base is to target person
Face picture carries out ageing processing.
In an embodiment, as shown in figure 8, the face ageing module includes at least:
The first adjustment module carries out first with face of the knowledge base to target face picture for sorting out according to face dimension
Secondary adjustment；
It specifically, should according to knowledge base if the target face picture is Leukemia in Southern Chinese Hans people and the age is 30 years old
Face two angulus oculi medialis distances at 60 years old are likely to reduce 1.0mm.
Second adjustment module carries out second to target face picture according to the face of parent and adjusts；Second of adjustment
Purpose is to meet genetic development.
Wrinkle treatment module selects the wrinkle texture in material database to shift for that will sort out by face dimension with knowledge base
To by second of target face picture adjusted；
Specifically, for women, deeper eye pouch is generally had after 50 years old, if the personality feature of user's input is
When " active love is laughed at ", then the user generally has smiling face and crow's feet after 40 years old.
Third, which adjusts module, makes wrinkle color and face color phase for wrinkle color and face color to be adjusted
Adaptation.
Final output be user different age group afterwards face picture.
In an embodiment, face ageing image processing system further includes customized adjusting judgment module, can be by defeated
Enter other information face ageing to be further processed.
When user other than inputting face picture without providing other information when, then only with from analyzing in face picture
The foundation that the information arrived is handled as subsequent face ageing；When user has input other information, then system can also further divide
It analyses these information and system is corrected.
The other information that user can input include but is not limited to father's face picture, mother's face picture, the age, race,
Ancestral home, personality feature.
It, be according to father's face picture, mother's face picture, age, race, ancestral after user has input other information
Face dimension obtained in nationality, personality feature information, supplement and correction step S3 is sorted out.
The present invention reduces ageing processing by combining the additional informations such as sex, race, parent's human face photo, personality
Error；On the other hand, the present invention also has the characteristics that convenience, including the additional informations such as parent's human face photo and personality be all can
Information is selected, these optional informations can be further reduced systematic error, but even if lacking part of optional information, the present invention is real
Existing precision has also exceeded traditional face ageing system.
The present invention also provides a kind of computer readable storage mediums, store computer program, and the computer program is located
The face ageing image processing method is executed when managing device operation.
The present invention also provides a kind of equipment, comprising:
Memory, for storing computer program；
Processor, for executing the computer program of the memory storage, so that the equipment executes the face
Ageing image processing method.
The above-described embodiments merely illustrate the principles and effects of the present invention, and is not intended to limit the present invention.It is any ripe
The personage for knowing this technology all without departing from the spirit and scope of the present invention, carries out modifications and changes to above-described embodiment.Cause
This, institute is complete without departing from the spirit and technical ideas disclosed in the present invention by those of ordinary skill in the art such as
At all equivalent modifications or change, should be covered by the claims of the present invention.
Claims (10)
1. a kind of face ageing image processing method, which is characterized in that the face ageing image processing method includes at least:
Obtain target face picture；
Feature extraction is carried out to the target face picture and obtains feature vector；
Described eigenvector is sorted out in different face dimensions, the face dimension includes at least age, gender, area
Domain/race；
It obtains the corresponding parent's face picture of the target face picture and extracts the face of parent；
Sorted out according to the face of the parent, face dimension and knowledge base carries out ageing processing to target face picture.
2. a kind of face ageing image processing method according to claim 1, which is characterized in that the acquisition target figure
Piece, comprising:
Acquire face picture；
Face datection is carried out to obtain human face region to be checked to the face picture；
Calculate the face quality point of face picture；
The face quality point is compared with face quality point threshold value, if the face quality point divides threshold in the face quality
It is worth in range, then the corresponding face picture of the face quality point is qualified picture；
Face critical point detection is carried out to the human face region to be checked；
Face normalization is carried out to obtain target face picture to face according to face key point.
3. a kind of face ageing image processing method according to claim 1, which is characterized in that the face dimension is also wrapped
Include personality, ancestral home, father's face picture, mother's face picture.
4. a kind of face ageing image processing method according to claim 3, which is characterized in that described according to the parent
Face, face dimension sorts out and knowledge base carries out ageing processing to target face picture, specifically include:
Sorted out according to face dimension and knowledge base carries out first time adjustment to the face of target face picture；
Second is carried out to target face picture according to the face of parent to adjust；
It will be sorted out by face dimension and knowledge base selects the wrinkle texture in material database to be transferred to by adjusted for the second time
Target face picture；
Wrinkle color and face color are adjusted, are adapted wrinkle color with face color.
5. a kind of face ageing image processing system, which is characterized in that the face ageing image processing system includes at least:
Target face picture acquisition module, for obtaining target face picture；
Characteristic extracting module obtains feature vector for carrying out feature extraction to the target face picture；
Face classifying module, for sorting out described eigenvector in different face dimensions, the face dimension is extremely
It less include age, gender, region/race；
Face extraction module, for obtaining the corresponding parent's face picture of the target face picture and extracting the five of parent
Official；
Face ageing module, for sorted out according to the face of the parent, face dimension and knowledge base to target face picture into
The ageing processing of row.
6. a kind of face ageing image processing method according to claim 1, which is characterized in that the target face picture
Acquisition module to including: less
Acquisition module, for acquiring face picture；
Face detection module, for carrying out Face datection to the face picture to obtain human face region to be checked；
Face quality divides computing module, for calculating the face quality point of face picture；
Comparison module, for the face quality point to be compared with face quality point threshold value, if the face quality point is in institute
It states face quality to divide in threshold range, then the corresponding face picture of the face quality point is qualified picture；
Critical point detection module, for carrying out face critical point detection to the human face region to be checked；
Face normalization module carries out face normalization to face according to face key point to obtain target face picture.
7. a kind of face ageing image processing method according to claim 1, which is characterized in that the face dimension is also wrapped
Include personality, ancestral home, father's face picture, mother's face picture.
8. a kind of face ageing image processing method according to claim 3, which is characterized in that the face ageing module
It includes at least:
The first adjustment module carries out first time tune with face of the knowledge base to target face picture for sorting out according to face dimension
It is whole；
Second adjustment module carries out second to target face picture according to the face of parent and adjusts；
Wrinkle treatment module, for will by face dimension sort out and knowledge base select material database in wrinkle texture be transferred to through
Cross second of target face picture adjusted；
Third, which adjusts module, is adapted wrinkle color with face color for wrinkle color and face color to be adjusted.
9. a kind of computer readable storage medium stores computer program, which is characterized in that the computer program is by processor
The face ageing image processing method as described in Claims 1 to 4 any one is executed when operation.
10. a kind of equipment characterized by comprising
Memory, for storing computer program；
Processor, for executing the computer program of the memory storage, so that the equipment executes such as Claims 1 to 4
Face ageing image processing method described in any one.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811268768.1A CN109509142A (en) | 2018-10-29 | 2018-10-29 | A kind of face ageing image processing method, system, readable storage medium storing program for executing and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811268768.1A CN109509142A (en) | 2018-10-29 | 2018-10-29 | A kind of face ageing image processing method, system, readable storage medium storing program for executing and equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109509142A true CN109509142A (en) | 2019-03-22 |
Family
ID=65746993
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811268768.1A Pending CN109509142A (en) | 2018-10-29 | 2018-10-29 | A kind of face ageing image processing method, system, readable storage medium storing program for executing and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109509142A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110287765A (en) * | 2019-05-06 | 2019-09-27 | 平安科技（深圳）有限公司 | Baby's appearance prediction technique, device and storage medium based on recognition of face |
| CN110335194A (en) * | 2019-06-28 | 2019-10-15 | 广州久邦世纪科技有限公司 | A kind of face ageing image processing method |
| CN110378230A (en) * | 2019-06-19 | 2019-10-25 | 平安科技（深圳）有限公司 | Missing face identification method, device, computer equipment and storage medium |
| CN111275610A (en) * | 2020-01-08 | 2020-06-12 | 杭州趣维科技有限公司 | Method and system for processing face aging image |
| CN112581356A (en) * | 2020-12-14 | 2021-03-30 | 广州岸边网络科技有限公司 | Portrait transformation processing method, device and storage medium |
| CN114708644A (en) * | 2022-06-02 | 2022-07-05 | 杭州魔点科技有限公司 | Face recognition method and system based on family gene template |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101556699A (en) * | 2008-11-07 | 2009-10-14 | 浙江大学 | Face-based facial aging image synthesis method |
| CN101755288A (en) * | 2007-07-23 | 2010-06-23 | 宝洁公司 | Method and apparatus for realistic simulation of wrinkle aging and de-aging |
| CN105787974A (en) * | 2014-12-24 | 2016-07-20 | 中国科学院苏州纳米技术与纳米仿生研究所 | Establishment method for establishing bionic human facial aging model |
| CN107491747A (en) * | 2017-08-08 | 2017-12-19 | 西南大学 | Face Forecasting Methodology based on regression analysis and wavelet transformation |
| CN108334886A (en) * | 2018-03-08 | 2018-07-27 | 殷韩 | Image prediction method, terminal device and readable storage medium storing program for executing |
| US20180293429A1 (en) * | 2017-03-30 | 2018-10-11 | George Mason University | Age invariant face recognition using convolutional neural networks and set distances |
-
2018
- 2018-10-29 CN CN201811268768.1A patent/CN109509142A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101755288A (en) * | 2007-07-23 | 2010-06-23 | 宝洁公司 | Method and apparatus for realistic simulation of wrinkle aging and de-aging |
| CN101556699A (en) * | 2008-11-07 | 2009-10-14 | 浙江大学 | Face-based facial aging image synthesis method |
| CN105787974A (en) * | 2014-12-24 | 2016-07-20 | 中国科学院苏州纳米技术与纳米仿生研究所 | Establishment method for establishing bionic human facial aging model |
| US20180293429A1 (en) * | 2017-03-30 | 2018-10-11 | George Mason University | Age invariant face recognition using convolutional neural networks and set distances |
| CN107491747A (en) * | 2017-08-08 | 2017-12-19 | 西南大学 | Face Forecasting Methodology based on regression analysis and wavelet transformation |
| CN108334886A (en) * | 2018-03-08 | 2018-07-27 | 殷韩 | Image prediction method, terminal device and readable storage medium storing program for executing |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110287765A (en) * | 2019-05-06 | 2019-09-27 | 平安科技（深圳）有限公司 | Baby's appearance prediction technique, device and storage medium based on recognition of face |
| CN110378230A (en) * | 2019-06-19 | 2019-10-25 | 平安科技（深圳）有限公司 | Missing face identification method, device, computer equipment and storage medium |
| WO2020252911A1 (en) * | 2019-06-19 | 2020-12-24 | 平安科技（深圳）有限公司 | Facial recognition method for missing individual, apparatus, computer device and storage medium |
| CN110378230B (en) * | 2019-06-19 | 2024-03-05 | 平安科技（深圳）有限公司 | Missing face recognition method, device, computer equipment and storage medium |
| CN110335194A (en) * | 2019-06-28 | 2019-10-15 | 广州久邦世纪科技有限公司 | A kind of face ageing image processing method |
| CN110335194B (en) * | 2019-06-28 | 2023-11-10 | 广州久邦世纪科技有限公司 | Face aging image processing method |
| CN111275610A (en) * | 2020-01-08 | 2020-06-12 | 杭州趣维科技有限公司 | Method and system for processing face aging image |
| CN111275610B (en) * | 2020-01-08 | 2023-08-18 | 杭州小影创新科技股份有限公司 | Face aging image processing method and system |
| CN112581356A (en) * | 2020-12-14 | 2021-03-30 | 广州岸边网络科技有限公司 | Portrait transformation processing method, device and storage medium |
| CN112581356B (en) * | 2020-12-14 | 2024-05-07 | 广州岸边网络科技有限公司 | Portrait transformation processing method, device and storage medium |
| CN114708644A (en) * | 2022-06-02 | 2022-07-05 | 杭州魔点科技有限公司 | Face recognition method and system based on family gene template |
| CN114708644B (en) * | 2022-06-02 | 2022-09-13 | 杭州魔点科技有限公司 | Face recognition method and system based on family gene template |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109509142A (en) | A kind of face ageing image processing method, system, readable storage medium storing program for executing and equipment | |
| CA2934514C (en) | System and method for identifying faces in unconstrained media | |
| CN104680121B (en) | Method and device for processing face image | |
| Sharma | Information Measure Computation and its Impact in MI COCO Dataset | |
| US20210027048A1 (en) | Human face image classification method and apparatus, and server | |
| CN105447441B (en) | Face authentication method and device | |
| Cament et al. | Face recognition under pose variation with local Gabor features enhanced by active shape and statistical models | |
| KR20230107415A (en) | Method for identifying an object within an image and mobile device for executing the method | |
| CN110569756A (en) | face recognition model construction method, recognition method, device and storage medium | |
| An et al. | An illumination normalization model for face recognition under varied lighting conditions | |
| CN107977660A (en) | Region of interest area detecting method based on background priori and foreground node | |
| CN104915684B (en) | A kind of image-recognizing method and device based on the more plane SVMs of robust | |
| CN110222718A (en) | The method and device of image procossing | |
| Kroon et al. | Eye localization in low and standard definition content with application to face matching | |
| Liu et al. | Iris recognition in visible spectrum based on multi-layer analogous convolution and collaborative representation | |
| US9940543B2 (en) | Control of computer vision pre-processing based on image matching using structural similarity | |
| CN109087240B (en) | Image processing method, image processing apparatus, and storage medium | |
| Xie et al. | Elastic shape-texture matching for human face recognition | |
| Shukla et al. | Deep Learning Model to Identify Hide Images using CNN Algorithm | |
| CN108268533A (en) | A kind of Image Feature Matching method for image retrieval | |
| Vishwakarma | A non-iterative learning based artificial neural network classifier for face recognition under varying illuminations | |
| CN106157280B (en) | A kind of image processing method and device | |
| Pun et al. | Skin Segmentation Using GMM Classifier and Texture Feature Extraction | |
| KR101436730B1 (en) | 3d face fitting method of unseen face using active appearance model | |
| Li et al. | Face detection using ellipsoid skin model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 401122 5 stories, Block 106, West Jinkai Avenue, Yubei District, Chongqing Applicant after: CHONGQING ZHONGKE YUNCONG TECHNOLOGY Co.,Ltd. Address before: 401122 5 stories, Block 106, West Jinkai Avenue, Yubei District, Chongqing Applicant before: CHONGQING ZHONGKE YUNCONG TECHNOLOGY Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190322 |
|
| RJ01 | Rejection of invention patent application after publication |