CN106295499B - Age estimation method and device - Google Patents
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The disclosure provides a kind of age estimation method and device.Disclosure age estimation method, comprising: obtain target facial image；Based on default face recognition algorithms, the corresponding facial image feature of target facial image is extracted；It is compared facial image feature has been stored in facial image feature and presetting database, obtains similarity；If similarity is greater than or equal to preset threshold, according to the corresponding age information of the facial image feature of storage for obtaining the similarity, the estimation age of target facial image is determined.The accuracy of age estimation can be improved in the disclosure.
Description
Technical field
This disclosure relates to computer technology more particularly to a kind of age estimation method and device.
Background technique
With the development of face recognition technology, age estimation can be identified according to facial image estimates the age of people
Meter.But use the associated age estimation method estimation age obtained, generally all float up and down in actual age, accuracy compared with
It is low.
Summary of the invention
To overcome the problems in correlation technique, the disclosure provides a kind of age estimation method and device.The technology
Scheme is as follows:
According to the first aspect of the embodiments of the present disclosure, a kind of age estimation method is provided, this method comprises: obtaining target person
Face image；Based on default face recognition algorithms, the corresponding facial image feature of the target facial image is extracted；By the face
Facial image feature has been stored in characteristics of image and presetting database to be compared, and obtains similarity；If the similarity is greater than
Or be equal to preset threshold, then according to the corresponding age information of the facial image feature of storage for obtaining the similarity, determine institute
State the estimation age of target facial image.
The technical scheme provided by this disclosed embodiment can include the following benefits: stored according to presetting database
The corresponding age information of facial image feature, determine with this stored facial image characteristic similarity be greater than preset threshold mesh
The estimation age of facial image is marked, to improve the accuracy of age estimation.
Optionally, above-mentioned according to the corresponding age information of the facial image feature of storage for obtaining the similarity, it determines
The estimation age of the target facial image may include: according to the facial image feature pair of storage for obtaining the similarity
The generation time of the date of birth and the target facial image answered, determine the estimation age of the target facial image.
Optionally, above-mentioned according to the corresponding age information of the facial image feature of storage for obtaining the similarity, it determines
The estimation age of the target facial image may include: according to the facial image feature pair of storage for obtaining the similarity
The generation time for the facial image answered, the facial image corresponding estimation age and the target facial image, determine described in
The estimation age of target facial image.
Optionally, above-mentioned according to the generation for having stored the corresponding facial image of facial image feature for obtaining the similarity
Time, the facial image corresponding estimation age and the target facial image, determine the estimation of the target facial image
Age may include: to obtain the first estimation age of the target facial image according to the target facial image；According to obtaining
The similarity stored the corresponding facial image of facial image feature generate time and the target facial image
The time is generated, first time difference is obtained；The first estimation age is subtracted into the first time difference, obtained for the second time
Difference；The mean value for calculating second time difference estimation age corresponding with the facial image, obtains the target face
The estimation age of image.
Optionally, after the estimation age of the above-mentioned determination target facial image, which can also be wrapped
It includes: storing estimation age of the target facial image and the target facial image to the presetting database.
The technical scheme provided by this disclosed embodiment can include the following benefits: by by target facial image and
The estimation age of target facial image store to presetting database, it can be achieved that in presetting database storing data continuous renewal,
So that the quantity of the facial image stored in presetting database is gradually increased and subsequent age estimated result is more smart
Really.
According to the second aspect of an embodiment of the present disclosure, a kind of age estimation device is provided, which includes: to obtain
Modulus block is configured as obtaining target facial image；Extraction module is configured as extracting institute based on default face recognition algorithms
It states and obtains the corresponding facial image feature of the target facial image that module obtains；Comparison module is configured as mentioning described
Facial image feature has been stored in the facial image feature and presetting database that modulus block extracts to be compared, and has been obtained similar
Degree；Processing module, if being configured as the similarity that the comparison module obtains is greater than or equal to preset threshold, basis is obtained
The corresponding age information of the facial image feature of storage for obtaining the similarity, determines the estimation year of the target facial image
Age.
The technical scheme provided by this disclosed embodiment can include the following benefits: stored according to presetting database
The corresponding age information of facial image feature, determine with this stored facial image characteristic similarity be greater than preset threshold mesh
The estimation age of facial image is marked, to improve the accuracy of age estimation.
Optionally, above-mentioned processing module includes: the first processing submodule, is configured as according to the acquisition similarity
The generation time for storing the corresponding date of birth of facial image feature and the target facial image, determine the target face figure
The estimation age of picture.
Optionally, above-mentioned processing module includes: second processing submodule, is configured as according to the acquisition similarity
Store generation time, the facial image corresponding estimation age and the target of the corresponding facial image of facial image feature
Facial image determines the estimation age of the target facial image.
Optionally, above-mentioned second processing submodule is configured as: according to the target facial image, obtaining the target person
The first estimation age of face image；According to the life for having stored the corresponding facial image of facial image feature for obtaining the similarity
At the generation time of time and the target facial image, first time difference is obtained；The first estimation age is subtracted into institute
First time difference is stated, the second time difference is obtained；Calculate second time difference estimation corresponding with the facial image
The mean value at age obtains the estimation age of the target facial image.
Optionally, above-mentioned age estimation device can also include: memory module, be configured as storing the target face figure
As and the target facial image the estimation age to the presetting database.
The technical scheme provided by this disclosed embodiment can include the following benefits: by by target facial image and
The estimation age of target facial image store to presetting database, it can be achieved that in presetting database storing data continuous renewal,
So that the quantity of the facial image stored in presetting database is gradually increased and subsequent age estimated result is more smart
Really.
In a kind of possible design, above-mentioned target facial image is the mobile device with camera function under preview mode
It obtains.
According to the third aspect of an embodiment of the present disclosure, a kind of age estimation device is provided, which includes: place
Manage device；For storing the memory of the processor-executable instruction；Wherein, the processor is configured to: obtain target person
Face image；Based on default face recognition algorithms, the corresponding facial image feature of the target facial image is extracted；By the face
Facial image feature has been stored in characteristics of image and presetting database to be compared, and obtains similarity；If the similarity is greater than
Or be equal to preset threshold, then according to the corresponding age information of the facial image feature of storage for obtaining the similarity, determine institute
State the estimation age of target facial image.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
In order to illustrate more clearly of the embodiment of the present disclosure or technical solution in the prior art, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Disclosed some embodiments without any creative labor, may be used also for those of ordinary skill in the art
To obtain other drawings based on these drawings.
Fig. 1 is a kind of flow chart of age estimation method shown according to an exemplary embodiment；
Fig. 2 is a kind of flow chart of the age estimation method shown according to another exemplary embodiment；
Fig. 3 is a kind of structural schematic diagram of age estimation device shown according to an exemplary embodiment；
Fig. 4 is a kind of structural schematic diagram of the age estimation device shown according to another exemplary embodiment；
Fig. 5 is a kind of structural schematic diagram of the age estimation device shown according to a further exemplary embodiment；
Fig. 6 is a kind of structural schematic diagram of age estimation device shown according to another exemplary embodiment；
Fig. 7 is a kind of age estimation device block diagram shown according to an exemplary embodiment.
Through the above attached drawings, it has been shown that the specific embodiment of the disclosure will be hereinafter described in more detail.These attached drawings
It is not intended to limit the scope of this disclosure concept by any means with verbal description, but is by referring to specific embodiments
Those skilled in the art illustrate the concept of the disclosure.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.
Term " first ", " second " in the specification and claims of the disclosure etc. are for distinguishing similar right
As without being used to describe a particular order or precedence order.It should be understood that the data used in this way in the appropriate case can be with
It exchanges, so that embodiment of the disclosure described herein for example can be with suitable other than those of illustrating or describing herein
Sequence is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that covering non-exclusive includes example
Such as, the process, method, system, product or equipment for containing a series of steps or units those of are not necessarily limited to be clearly listed
Step or unit, but may include being not clearly listed or intrinsic for these process, methods, product or equipment other
Step or unit.
Fig. 1 is a kind of flow chart of age estimation method shown according to an exemplary embodiment.The present embodiment provides one
Kind of age estimation method, this method can be executed by age estimation device, which can be by hardware and/or soft
The mode of part is realized, and can be integrated in mobile device, which can be smart phone or tablet computer or a number
The electronic equipments such as word assistant (Personal Digital Assistant, referred to as: PDA).As shown in Figure 1, the age estimation side
Method the following steps are included:
In a step 101, target facial image is obtained.
Target facial image is obtained by the mobile device acquisition with camera function.For example, target facial image can
Think what the mobile device with camera function obtained under preview mode.When user is in the coverage of mobile device,
Mobile device can search for automatically and shoot the facial image of user.
Target facial image can be still image or dynamic image.Wherein, dynamic image includes user in different positions
It sets and/or different expression, image in different positions.
It can be according to the relevant technologies, to still image or the advanced row recognition of face of dynamic image, such as to every in video
One frame image carries out recognition of face, if recognizing includes face in a certain frame image, intercepting includes face in the image
Image as target facial image.
In addition, can be pre-processed to target facial image after obtaining target facial image.This is because initially
Original image limited by various conditions and random disturbances, tend not to directly use, therefore original image need to be carried out
The image preprocessings such as gray correction, noise filtering.For facial image, preprocessing process mainly includes facial image
Light compensation, greyscale transformation, histogram equalization, normalization, geometric correction, filtering and sharpening etc..
In a step 102, based on default face recognition algorithms, it is special to extract the corresponding facial image of the target facial image
Sign.
Wherein, default face recognition algorithms can be specially recognizer based on features of human face images, based on whole picture
The recognizer of facial image, the recognizer based on template or the algorithm identified using neural network, etc..
Facial image feature is, for example, histogram feature, color characteristic, template characteristic, structure feature and Haar feature etc..
Facial image feature extraction is the process that feature modeling is carried out to face.The method of facial image feature extraction can
Think Knowledge based engineering characterizing method.Knowledge based engineering characterizing method is mainly the shape description and face according to human face
The distance between organ characteristic facilitates the characteristic of face classification to obtain, and characteristic component generally includes between characteristic point
Euclidean distance, curvature and angle etc..Face is locally made of eyes, nose, mouth, chin etc., between these parts and they
The geometric description of structural relation can be used as the important feature of identification face.
In step 103, facial image feature will have been stored in facial image feature and presetting database to be compared, obtained
Obtain similarity.
The step carries out facial image feature stored in facial image feature to be identified and presetting database
Compare, obtains similarity.This process can be divided into two classes: one kind is confirmation, is the one-to-one process for carrying out image comparison；Separately
One kind is identification, is the one-to-many process for carrying out images match comparison.
Wherein, presetting database may include facial image, the corresponding facial image feature of the facial image and the people
The corresponding age information of face image, the age information can be the date of birth that user marks in advance, be also possible to according to the people
The face image corresponding estimation age, alternatively, the combination at both date of birth and estimation age.Optionally, which may be used also
To include the identity marks of user, such as name or ID card No., etc..Presetting database can be by largely training number
It obtains according to statistics.
Illustratively, presetting database can be specially face photograph album.Face photograph album refers to using image analysis technology, certainly
Dynamicly cloud photograph album photo content is carried out to carry out taxonomic revision according to face, so that the photo of a people all be arranged together.
Meanwhile user can mark the information such as everyone name and age in face photograph album.
At step 104, if the similarity is greater than or equal to preset threshold, according to the storage people for obtaining the similarity
The corresponding age information of face image feature determines the estimation age of target facial image.
Similarity is greater than or equal to preset threshold and illustrates target facial image and at least face figure in presetting database
As being the same person.Due to being stored with the corresponding age information of facial image in presetting database, the disclosure can be according to obtaining
The corresponding age information of the facial image feature of storage for obtaining the similarity, determines the estimation age of target facial image.
For example, a facial image is stored in presetting database, the corresponding facial image feature of the facial image and target
The similarity of the corresponding facial image feature of facial image is greater than preset threshold, illustrates the face figure stored in presetting database
As being the same person with target facial image.At this point, being believed according to the facial image stored in presetting database corresponding age
Breath, such as age information are date of birth, to determine the estimation age of target facial image.
In conclusion age estimation method provided in this embodiment, special according to the stored facial image of presetting database
It levies corresponding age information, determines and the target facial image for having stored facial image characteristic similarity greater than preset threshold
The age is estimated, to improve the accuracy of age estimation.
On the basis of the above embodiments, above-mentioned according to the facial image feature of the storage corresponding year for obtaining the similarity
Age information determines the estimation age of target facial image, can be accomplished in several ways, is exemplified below explanation:
In a kind of specific implementation, believed according to the facial image feature of storage for the obtaining the similarity corresponding age
Breath determines that the estimation age of target facial image may include: according to the facial image feature pair of storage for obtaining the similarity
The generation time of the date of birth and target facial image answered determines the estimation age of target facial image.
For example, the corresponding date of birth of the facial image feature of storage for obtaining the similarity is on May 1st, 2016, mesh
The generation time for marking facial image is on July 1st, 2016, it is determined that the estimation age of target facial image is 62 days 0 year.
In another specific implementation, believed according to the facial image feature of storage for the obtaining the similarity corresponding age
Breath determines that the estimation age of target facial image may include: according to the facial image feature pair of storage for obtaining the similarity
The generation time for the facial image answered, the facial image corresponding estimation age and target facial image, determine target face figure
The estimation age of picture.
Wherein, according to obtain the similarity the generation time for having stored the corresponding facial image of facial image feature, should
Facial image corresponding estimation age and target facial image, determine the estimation age of target facial image, can be with specifically: root
According to target facial image, the first estimation age of target facial image is obtained；According to the face figure of storage for obtaining the similarity
As the generation time of the generation time and target facial image of the corresponding facial image of feature, first time difference is obtained；By
One estimation age subtracted first time difference, obtained the second time difference；It is corresponding with facial image to calculate the second time difference
The mean value for estimating the age, obtains the estimation age of target facial image.
For example, it is assumed that the generation time of the facial image is on May 1st, 2016, the facial image corresponding estimation age
The generation time for 25 years, target facial image be on July 1st, 2016, target facial image first estimation the age be 27 years,
Obtain that first time difference is 62 days, the second time difference is 303 days 26 years, the estimation age of target facial image is 25 years
334 days.
Above example is illustrated by taking a facial image as an example, but the disclosure is not limited system.That is, being somebody's turn to do
The corresponding facial image of the facial image feature of storage of similarity can be one or more, and those skilled in the art can manage
Solution, when obtain the similarity the corresponding facial image of the facial image feature of storage it is more, the target face figure finally obtained
The estimation age of picture is also relatively more accurate.
It should be noted that " date of birth " that is referred in each embodiment of the disclosure, " generate time ", " estimation age ", " the
One time difference " etc., unit is identical, in order to calculate.
Fig. 2 is a kind of flow chart of the age estimation method shown according to another exemplary embodiment.This method can be by
Age estimation device executes, which can be realized by way of hardware and/or software, and can be integrated in movement
In equipment, which can be smart phone or the electronic equipments such as tablet computer or PDA.As shown in Fig. 2, shown in Fig. 1
On the basis of process, the age estimation method can with the following steps are included:
In step 201, if similarity, which is less than preset threshold, determines target facial image according to target facial image
The estimation age.
It is appreciated that the first estimation age in estimation age, that is, above-described embodiment of goal facial image.
Since similarity is less than preset threshold, illustrate that not stored in presetting database with the target facial image is same
Therefore the facial image of people determines the estimation age of target facial image according to the relevant technologies.
Optionally, if similarity is less than preset threshold, target tracking algorism can be used to the corresponding people of target facial image
Face carries out real-time tracking.Face is tracked using target tracking algorism, can get the position of face in each frame image, no
The age is estimated with repetition is carried out, and improves speed.
Further, the age estimation method can with the following steps are included:
In step 202, estimation age of target facial image and target facial image is stored to presetting database.
In conclusion age estimation method provided in this embodiment, by by target facial image and target facial image
The estimation age store to presetting database, it can be achieved that in presetting database storing data continuous renewal so that default
The quantity of the facial image stored in database is gradually increased and subsequent age estimated result is more accurate.
Following is embodiment of the present disclosure, can be used for executing embodiments of the present disclosure.It is real for disclosure device
Undisclosed details in example is applied, embodiments of the present disclosure is please referred to.
Fig. 3 is a kind of structural schematic diagram of age estimation device shown according to an exemplary embodiment.It, should referring to Fig. 3
Age estimation device 30 includes obtaining module 31, extraction module 32, comparison module 33 and processing module 34.
The acquisition module 31 is configured as obtaining target facial image.
The extraction module 32 is configured as being extracted based on default face recognition algorithms and being obtained the target person that module 31 obtains
The corresponding facial image feature of face image.
The comparison module 33 is configured as to have deposited in facial image feature and presetting database that extraction module 32 extracts
Storage facial image feature is compared, and obtains similarity.
The processing module 34, if the similarity for being configured as the acquisition of comparison module 33 is greater than or equal to preset threshold, root
According to the corresponding age information of the facial image feature of storage for obtaining the similarity, the estimation age of target facial image is determined.
In conclusion age estimation device provided in this embodiment, special according to the stored facial image of presetting database
It levies corresponding age information, determines and the target facial image for having stored facial image characteristic similarity greater than preset threshold
The age is estimated, to improve the accuracy of age estimation.
Fig. 4 is a kind of structural schematic diagram of the age estimation device shown according to another exemplary embodiment.Reference Fig. 4,
On the basis of structure shown in Fig. 3, in a kind of implementation, processing module 34 includes: the first processing submodule 341.
The first processing submodule 341, is configured as according to the facial image feature pair of storage for obtaining the similarity
The generation time of the date of birth and target facial image answered determines the estimation age of target facial image.
In another implementation, processing module 34 includes: second processing submodule 342.
The second processing submodule 342 is configured as according to the facial image feature pair of storage for obtaining the similarity
The generation time for the facial image answered, the facial image corresponding estimation age and target facial image, determine target face
The estimation age of image.
In the implementation, further, second processing submodule 342 is configured as: according to the target facial image,
Obtain the first estimation age of the target facial image；It is corresponding according to the facial image feature of storage for obtaining the similarity
Facial image generation time and the target facial image the generation time, obtain first time difference；By described first
The estimation age subtracts the first time difference, obtains the second time difference；Calculate second time difference and the face
The mean value at image corresponding estimation age, obtains the estimation age of the target facial image.
Fig. 5 is a kind of structural schematic diagram of the age estimation device shown according to a further exemplary embodiment.Reference Fig. 5,
On the basis of structure shown in Fig. 3, age estimation device 40 can also include another processing module 41 and tracking module 42.Its
In, tracking module 42 is optional module, that is to say, that age estimation device 40 can not also include tracking module 42.
The processing module 41, if the similarity for being configured as the acquisition of comparison module 33 is less than the preset threshold,
According to target facial image, the estimation age of target facial image is determined.
The tracking module 42 is adopted if the similarity for being configured as the acquisition of comparison module 33 is less than the preset threshold
The corresponding face of target facial image is tracked with target tracking algorism.
In conclusion age estimation device provided in this embodiment, using target tracking algorism to face carry out in real time with
Track can get the position of face in each frame image, repeats to estimate the age without carrying out, improves speed.
Fig. 6 is a kind of structural schematic diagram of age estimation device shown according to another exemplary embodiment.Reference Fig. 6,
It (is illustrated by taking Fig. 3 as an example here) on the basis of the structure shown in Fig. 3 or Fig. 4 or Fig. 5, age estimation device 50 can also wrap
Include memory module 51.
The memory module 51 is configured as the estimation age of storage target facial image and target facial image to present count
According to library.
If for the structure shown in Fig. 5, memory module is coupled with processing module 34 and processing module 41 respectively.
In conclusion age estimation device provided in this embodiment, by by target facial image and target facial image
The estimation age store to presetting database, it can be achieved that in presetting database storing data continuous renewal so that default
The quantity of the facial image stored in database is gradually increased and subsequent age estimated result is more accurate.
In the above-described embodiments, target facial image is that the mobile device with camera function obtains under preview mode
's.
It should be noted that the function of acquisition module mentioned by the embodiment of the present disclosure and functioning as in mobile device
Receiver, extraction module, tracking module, processing module function and function as the processor in mobile device, compare
It the function of module and functions as the processor or comparator in mobile device, the function of memory module and functions as shifting
Memory in dynamic equipment.
Fig. 7 is a kind of age estimation device block diagram shown according to an exemplary embodiment.Referring to Fig. 7, age estimation dress
Setting 800 may include following one or more components: processing component 802, memory 804, power supply module 806, multimedia component
808, audio component 810, input/output (input/output, referred to as: I/O) interface 812, sensor module 814, Yi Jitong
Believe component 816.
Processing component 802 usually control age estimation device 800 integrated operation, such as with display, data communication, camera
Operation and record operate associated operation.Processing component 802 may include one or more processors 820 to execute instruction,
To perform all or part of the steps of the methods described above.In addition, processing component 802 may include one or more modules, it is convenient for
Interaction between processing component 802 and other assemblies.For example, processing component 802 may include multi-media module, to facilitate more matchmakers
Interaction between body component 808 and processing component 802.
Memory 804 is configured as storing various types of data to support the operation in age estimation device 800.These
The example of data includes the instruction of any application or method for operating on age estimation device 800, contacts number
According to, telephone book data, message, picture, video etc..Memory 804 can be by any kind of volatibility or non-volatile memories
Equipment or their combination realize, as static random access memory (Static Random Access Memory, referred to as:
SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only
Memory, referred to as: EEPROM), Erasable Programmable Read Only Memory EPROM (Erasable Programmable Read Only
Memory, referred to as: EPROM), programmable read only memory (Programmable Red-Only Memory, referred to as: PROM),
Read-only memory (Read-Only Memory, referred to as: ROM), magnetic memory, flash memory, disk or CD.
Power supply module 806 provides electric power for the various assemblies of age estimation device 800.Power supply module 806 may include electricity
Management system, one or more power supplys and other are associated with electric power is generated, managed, and distributed for age estimation device 800
Component.
Multimedia component 808 includes one output interface of offer between the age estimation device 800 and user
Screen.In some embodiments, screen may include liquid crystal display (Liquid Crystal Display, referred to as: LCD) and
Touch panel (Touch Panel, referred to as: TP).If screen includes touch panel, screen may be implemented as touch screen, with
Receive input signal from the user.Touch panel includes one or more touch sensors to sense touch, sliding and touch
Gesture on panel.The touch sensor can not only sense the boundary of a touch or slide action, but also detect with it is described
Touch or the relevant duration and pressure of slide.In some embodiments, multimedia component 808 includes one and preposition takes the photograph
As head and/or rear camera.It is such as in a shooting mode or a video mode, preposition when age estimation device 800 is in operation mode
Camera and/or rear camera can receive external multi-medium data.Each front camera and rear camera can be with
Be a fixed optical lens system or have focusing and optical zoom capabilities.
Audio component 810 is configured as output and/or input audio signal.For example, audio component 810 includes a Mike
Wind (Microphone, referred to as: MIC), when age estimation device 800 is in operation mode, such as call model, logging mode and language
When sound recognition mode, microphone is configured as receiving external audio signal.The received audio signal can be further stored
It is sent in memory 804 or via communication component 816.In some embodiments, audio component 810 further includes a loudspeaker,
For output audio signal.
I/O interface 812 provides interface between processing component 802 and peripheral interface module, and above-mentioned peripheral interface module can
To be keyboard, click wheel, button etc..These buttons may include, but are not limited to: home button, volume button, start button and lock
Determine button.
Sensor module 814 includes one or more sensors, for providing various aspects for age estimation device 800
Status assessment.For example, sensor module 814 can detecte the state that opens/closes to age estimation device 800, the phase of component
To positioning, such as the component is the display and keypad of age estimation device 800, and sensor module 814 can also detect
The position change of 800 1 components of age estimation device 800 or age estimation device, user contact with age estimation device 800
Existence or non-existence, the temperature change in 800 orientation of age estimation device or acceleration/deceleration and age estimation device 800.Sensing
Device assembly 814 may include proximity sensor, be configured to detect depositing for neighbouring object without any physical contact
?.Sensor module 814 can also include optical sensor, such as complementary metal oxide semiconductor (Complementary Metal
Oxide Semiconductor, referred to as: CMOS) or charge coupled cell (Charge-coupled Device, referred to as: CCD)
Photosensitive imaging element, for being used in imaging applications.In some embodiments, which can also include adding
Velocity sensor, gyro sensor, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 816 is configured to facilitate wired or wireless way between age estimation device 800 and other equipment
Communication.Age estimation device 800 can access the wireless network based on communication standard, such as Wireless Fidelity (Wireless-
Fidelity, referred to as: Wi-Fi), 2G or 3G or their combination.In one exemplary embodiment, communication component 816 via
Broadcast channel receives broadcast singal or broadcast related information from external broadcasting management system.In an exemplary embodiment
In, the communication component 816 further includes near-field communication (Near Field Communication, referred to as: NFC) module, to promote
Into short range communication.For example, NFC module can based on radio frequency identification (Radio Frequency Identification, referred to as:
RFID) technology, Infrared Data Association (Infrared Data Association, referred to as: IrDA) technology, ultra wide band (Ultra
Wideband, referred to as: UWB) technology, bluetooth (Bluetooth, referred to as: BT) technology and other technologies are realized.
In the exemplary embodiment, age estimation device 800 can be by one or more application specific integrated circuit
(Application Specific Integrated Circuit, referred to as: ASIC), digital signal processor (Digital
Signal Processor, referred to as: DSP), digital signal processing appts (Digital Signal Processing Device,
Referred to as: DSPD), programmable logic device (Programmable Logic Device, referred to as: PLD), field-programmable gate array
Column (Field Programmable Gate Array, referred to as: FPGA), controller, microcontroller, microprocessor or other electricity
Subcomponent is realized, for executing the above method.
In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instruction, example are additionally provided
It such as include the memory 804 of instruction, above-metioned instruction can be executed by the processor 820 of age estimation device 800 to complete above-mentioned side
Method.For example, the non-transitorycomputer readable storage medium can be ROM, random access memory (Random Access
Memory, referred to as: RAM), CD-ROM (Compact Disc Read-Only Memory, referred to as: CD-ROM), tape, soft
Disk and optical data storage devices etc..
A kind of non-transitorycomputer readable storage medium, when the instruction in the storage medium is by age estimation device
When 800 processor executes, so that age estimation device 800 is able to carry out a kind of age estimation method, which comprises obtain
Take target facial image；Based on default face recognition algorithms, the corresponding facial image feature of the target facial image is extracted；It will
Facial image feature has been stored in the facial image feature and presetting database to be compared, and obtains similarity；If the phase
It is greater than or equal to preset threshold like degree, then is believed according to the facial image feature of storage for the obtaining the similarity corresponding age
Breath, determines the estimation age of the target facial image.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to its of the disclosure
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following
Claims are pointed out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by appended claims
System.
Claims (8)
1. a kind of age estimation method characterized by comprising
Obtain target facial image；
Based on default face recognition algorithms, the corresponding facial image feature of the target facial image is extracted；
It is compared facial image feature has been stored in the facial image feature and presetting database, obtains similarity；
If the similarity is greater than or equal to preset threshold, according to the facial image feature pair of storage for obtaining the similarity
The age information answered determines the estimation age of the target facial image；
Wherein, described according to the corresponding age information of the facial image feature of storage for obtaining the similarity, determine the mesh
Mark the estimation age of facial image, comprising:
According to the generation time for having stored the corresponding facial image of facial image feature for obtaining the similarity, the face figure
As corresponding estimation age and the target facial image, the estimation age of the target facial image is determined；
The generation time for having stored the corresponding facial image of facial image feature according to the acquisition similarity, the people
Face image corresponding estimation age and the target facial image, determine the estimation age of the target facial image, comprising:
According to the target facial image, the first estimation age of the target facial image is obtained；
According to the generation time for having stored the corresponding facial image of facial image feature and the target for obtaining the similarity
The generation time of facial image, obtain first time difference；
The first estimation age is subtracted into the first time difference, obtains the second time difference；
The mean value for calculating second time difference estimation age corresponding with the facial image, obtains the target face figure
The estimation age of picture.
2. the method according to claim 1, wherein described according to the face figure of storage for obtaining the similarity
As the corresponding age information of feature, the estimation age of the target facial image is determined, comprising:
The corresponding date of birth of facial image feature and the target facial image have been stored according to obtain the similarity
The time is generated, determines the estimation age of the target facial image.
3. method according to claim 1 or 2, which is characterized in that the estimation year of the determination target facial image
After age, the method also includes:
Estimation age of the target facial image and the target facial image is stored to the presetting database.
4. method according to claim 1 or 2, which is characterized in that the target facial image is with camera function
What mobile device obtained under preview mode.
5. a kind of age estimation device characterized by comprising
Module is obtained, is configured as obtaining target facial image；
Extraction module is configured as extracting the target face for obtaining module and obtaining based on default face recognition algorithms
The corresponding facial image feature of image；
Comparison module is configured as the facial image feature for extracting the extraction module and has stored in presetting database
Facial image feature is compared, and obtains similarity；
Processing module, if being configured as the similarity that the comparison module obtains is greater than or equal to preset threshold, basis
The corresponding age information of the facial image feature of storage for obtaining the similarity, determines the estimation year of the target facial image
Age；
Wherein, the processing module includes:
Second processing submodule is configured as according to the corresponding face figure of the facial image feature of storage for obtaining the similarity
The generation time of picture, the facial image corresponding estimation age and the target facial image, determine the target face figure
The estimation age of picture；
The second processing submodule is configured as:
According to the target facial image, the first estimation age of the target facial image is obtained；
According to the generation time for having stored the corresponding facial image of facial image feature and the target for obtaining the similarity
The generation time of facial image, obtain first time difference；
The first estimation age is subtracted into the first time difference, obtains the second time difference；
The mean value for calculating second time difference estimation age corresponding with the facial image, obtains the target face figure
The estimation age of picture.
6. device according to claim 5, which is characterized in that the processing module includes:
First processing submodule, when being configured as birth corresponding according to the facial image feature of storage for obtaining the similarity
Between and the target facial image the generation time, determine the estimation age of the target facial image.
7. device according to claim 5 or 6, which is characterized in that described device further include:
Memory module is configured as storing estimation age of the target facial image and the target facial image to described pre-
If database.
8. device according to claim 5 or 6, which is characterized in that the target facial image is with camera function
What mobile device obtained under preview mode.
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| CN107194868A (en) * | 2017-05-19 | 2017-09-22 | 成都通甲优博科技有限责任公司 | A kind of Face image synthesis method and device |
| CN107192542B (en) * | 2017-05-19 | 2019-06-25 | 北京车和家信息技术有限责任公司 | Feel detection device, method, system, computer equipment and readable storage medium storing program for executing |
| EP3648008A4 (en) * | 2017-06-30 | 2020-07-08 | Guangdong Oppo Mobile Telecommunications Corp., Ltd. | Face recognition method and apparatus, storage medium, and electronic device |
| CN107590464A (en) * | 2017-09-12 | 2018-01-16 | 广东欧珀移动通信有限公司 | Face identification method and Related product |
| CN108197592B (en) * | 2018-01-22 | 2022-05-27 | 百度在线网络技术（北京）有限公司 | Information acquisition method and device |
| CN109190449A (en) * | 2018-07-09 | 2019-01-11 | 北京达佳互联信息技术有限公司 | Age recognition methods, device, electronic equipment and storage medium |
| CN109459722A (en) * | 2018-10-23 | 2019-03-12 | 同济大学 | Voice interactive method based on face tracking device |
| CN110008926B (en) * | 2019-04-15 | 2020-06-26 | 北京字节跳动网络技术有限公司 | Method and device for identifying age |
| CN110909597A (en) * | 2019-10-14 | 2020-03-24 | 深圳市元征科技股份有限公司 | Vehicle child lock falling control method and device and vehicle-mounted equipment |
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