CN107831907A - Identity identifying method and device based on Gait Recognition - Google Patents
Identity identifying method and device based on Gait Recognition Download PDFInfo
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Abstract
The present invention relates to identity identifying technology field, and in particular to a kind of identity identifying method and device based on Gait Recognition, this method include：Obtain the multiple acceleration informations for the acceleration transducer collection being arranged at user, the multiple acceleration transducer data are carried out with analysis and extracts at least one gait cycle, calculate the matching degree average of at least one gait cycle and default gait cycle template, if matching degree average is more than predetermined threshold value, pass through authentication.This programme extracts gait cycle by gathering multiple acceleration informations in user's walking process after analyzing the plurality of acceleration information, further to be matched each gait cycle with default gait cycle template.Due to being to gather multiple acceleration informations respectively for different users and calculate gait cycle, therefore, the individual difference of different user is preferably met, improve the degree of accuracy of the authentication based on Gait Recognition.
Description
Technical field
The present invention relates to identity identifying technology field, in particular to a kind of authentication side based on Gait Recognition
Method and device.
Background technology
Identity identifying method based on Gait Recognition was most proposed that he is by largely repeating reality earlier than 2006 by Gafurov
The difference between gait similitude and the different user between now same user is issued after examination and approval, and is drawn a conclusion：Based on all limbs
The motion of body, gait are unique, therefore available for the authentication of user.In the prior art, based on Gait Recognition
Method mainly has three classes：Based on machine vision, based on ground transaucer, based on wearable sensor.Wherein, regarded based on machine
Feel is the gait pattern image during being walked using video camera capture sequence of user, is then realized using image matching algorithm
Authentication, easy light, block, the influence of distance；Based on ground transaucer be by floor in carpet in force snesor
The gait feature of user is captured, is easily affected by；Analyzed based on wearable sensor using acceleration signal
Gait uniqueness.At three kinds in the prior art, it is best one kind based on wearable sensor, but deposits in the prior art
The problem of not accurate is being detected, its reason is to make user walk with fixed speed when detecting, and does not account for the leg speed of user
Change, have ignored the individual difference of user.Therefore it provides a kind of more accurately identity identifying method based on Gait Recognition is
Extremely it is necessary.
The content of the invention
It is an object of the invention to provide a kind of identity identifying method based on Gait Recognition, is more accurately based on realizing
Gait Recognition carries out authentication.
Another object of the present invention is to provide a kind of identification authentication system based on Gait Recognition, to realize more accurately
Authentication is carried out based on Gait Recognition.
To achieve these goals, the technical scheme that the embodiment of the present invention uses is as follows：
In a first aspect, the embodiments of the invention provide identity identifying method of the kind based on Gait Recognition, methods described includes：
Obtain the acceleration transducer being arranged at user and gather multiple acceleration informations；The multiple acceleration information is divided
At least one gait cycle is extracted in analysis；Calculate at least one gait cycle and the matching degree of default gait cycle template is equal
Value；If the matching degree average is more than predetermined threshold value, pass through authentication.
Second aspect, the embodiment of the present invention additionally provide a kind of identification authentication system based on Gait Recognition, described device
Including：Acquisition module, for obtaining multiple acceleration informations of the acceleration transducer being arranged at user collection；Analyze mould
Block, at least one gait cycle is extracted for carrying out analysis to the multiple acceleration information；Computing module, it is described for calculating
At least one gait cycle and the matching degree average of default gait cycle template；Comparison module, if for the matching degree average
More than predetermined threshold value, then pass through authentication.
A kind of identity identifying method and device based on Gait Recognition provided in an embodiment of the present invention, this method include：Obtain
The multiple acceleration informations for taking the acceleration transducer being arranged at user to gather, to the multiple acceleration transducer data
Carry out analysis and extract at least one gait cycle, calculate at least one gait cycle and the matching of default gait cycle template
Average is spent, if matching degree average is more than predetermined threshold value, passes through authentication.This programme is by gathering in user's walking process
Multiple acceleration informations, and gait cycle is extracted after analyzing the plurality of acceleration information, so that further each to be walked
The state cycle is matched with default gait cycle template.Due to being to gather multiple acceleration informations respectively simultaneously for different users
Gait cycle is calculated, therefore, the individual difference of different user is preferably met, improves the identity based on Gait Recognition and recognize
The degree of accuracy of card.
To enable the above objects, features and advantages of the present invention to become apparent, preferred embodiment cited below particularly, and coordinate
Appended accompanying drawing, is described in detail below.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by embodiment it is required use it is attached
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore be not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 shows a kind of structural representation of terminal device provided in an embodiment of the present invention.
Fig. 2 shows a kind of flow signal of identity identifying method based on Gait Recognition provided in an embodiment of the present invention
Figure.
Fig. 3 shows a kind of stream of the sub-step of identity identifying method based on Gait Recognition provided in an embodiment of the present invention
Journey schematic diagram.
Fig. 4 shows a kind of another sub-step of identity identifying method based on Gait Recognition provided in an embodiment of the present invention
Schematic flow sheet.
Fig. 5 shows a kind of schematic diagram of one sided spectral density function provided in an embodiment of the present invention.
Fig. 6 shows a kind of another sub-step of identity identifying method based on Gait Recognition provided in an embodiment of the present invention
Schematic flow sheet.
Fig. 7 shows a kind of acceleration information statistical chart provided in an embodiment of the present invention.
Fig. 8 shows the schematic diagram of gait cycle Detection accuracy provided in an embodiment of the present invention.
Fig. 9 shows the schematic diagram of identification accuracy rate provided in an embodiment of the present invention.
Figure 10 shows that the functional module of identification authentication system of the kind provided in an embodiment of the present invention based on Gait Recognition is shown
It is intended to.
Diagram：100- terminal devices；Identification authentication systems of the 110- based on Gait Recognition；120- memories；130- is stored
Controller；140- processors；150- Peripheral Interfaces；160- input-output units；170- audio units；180- display units；
190- communication units；111- acquisition modules；112- analysis modules；113- processing modules；114- computing modules；115- compares mould
Block.
Embodiment
Below in conjunction with accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.Generally exist
The component of the embodiment of the present invention described and illustrated in accompanying drawing can be configured to arrange and design with a variety of herein.Cause
This, the detailed description of the embodiments of the invention to providing in the accompanying drawings is not intended to limit claimed invention below
Scope, but it is merely representative of the selected embodiment of the present invention.Based on embodiments of the invention, those skilled in the art are not doing
The every other embodiment obtained on the premise of going out creative work, belongs to the scope of protection of the invention.
It should be noted that：Similar label and letter represents similar terms in following accompanying drawing, therefore, once a certain Xiang Yi
It is defined, then it further need not be defined and explained in subsequent accompanying drawing in individual accompanying drawing.Meanwhile the present invention's
In description, term " first ", " second " etc. are only used for distinguishing description, and it is not intended that instruction or hint relative importance.
The fast development of Wearable in recent years, a variety of applications such as medical treatment, rehabilitation, interactive game have been widely used in it
Field.Many sensors, as inertial sensor, Magnetic Sensor, barometertic altimeter have been integrated with most of Wearables (such as
Smart phone or intelligent watch etc.) in so that Wearable more intelligence and it is powerful.Similarly, with Wearable
Function it is stronger and stronger, then more private informations will be stored in the Wearable, such as the communication information, private photos, will be regarded
Frequency etc., thus, safety and secret protection become an important need of Wearable.It is existing for Wearable
Safety and secret protection mainly include two methods, and a kind of is traditional password encryption, and another kind is biological authentication method.Its
In, there is the problems such as password is easily stolen, is easily cracked in traditional password encryption, it is impossible to ensure the peace of Wearable well
Entirely；In addition, increasing with Wearable, password easily passes out of mind so that user is not convenient to use Wearable.The life
Thing authentication method includes fingerprint recognition and recognition of face, and its confidentiality is preferable, but needs user's cooperation just can be encrypted or solve
It is close, and continuous certification can not be carried out.As can be seen here, existing two kinds of methods protected to safety and privacy still have scarce
Fall into.
It it is mainly adding to the acceleration transducer collection in Wearable for the authentication based on Gait Recognition
Speed data is analyzed to carry out authentication, and it, which has, does not need user to cooperate with one's own initiative and identify more accurately characteristic.
Gait Recognition is mainly that the posture walked by user identifies the identity of people, because everyone gait is different, therefore
The purpose of identification can be played.The reason is that from the interpretation of biomethanics, gait is numerous muscle and the pass of people
The aggregate motion of section, body structure parameter can be described as, everyone body structure is different and is related to hundreds of variables, because
This, everyone gait is unique, and therefore, gait can be used for carrying out people authentication, and with because being difficult to pretend
With imitating to cause identification more accurately advantage.
Authentication usage scenario based on Gait Recognition is very wide, and it can be used for the Code in Hazardous Special Locations such as prison, airport, bank
Access control and secure authentication, also there is potential application value in terms of intelligent vision monitoring, can be also used for public security machine
Close criminal investigation and specific objective search etc..If robber is made up when robbing the bank, worn a mask or easily held etc. and dressed up,
Then the monitoring camera of bank can not gather the true appearance of robber, or even can not find the fingerprint of robber in scene of a crime,
Then now authentication can be carried out by the walking postures of robber, to distinguish identity, to help police to solve a case as early as possible.
A kind of identity identifying method based on Gait Recognition provided in an embodiment of the present invention is applied to terminal device, the terminal
Equipment may be, but not limited to, the intelligent electronic device such as computer.Fig. 1 is refer to, is a kind of terminal provided in an embodiment of the present invention
The structural representation of equipment 100.The terminal device 100 include the identification authentication system 110 based on Gait Recognition, memory 120,
Storage control 130, processor 140, Peripheral Interface 150, input input block 160, audio unit 170, display unit 180 with
And communication unit 190, wherein,
The memory 120, storage control 130, processor 140, Peripheral Interface 150, input-output unit 160, sound
Frequency unit 170, display unit 180,190 each element of communication unit are directly or indirectly electrically connected between each other, to realize number
According to transmission or interaction.For example, these elements can be realized electrically by one or more communication bus or signal wire between each other
Connection.The identification authentication system 110 based on Gait Recognition include it is at least one can be with software or firmware (firmware)
Form is stored in the memory 120 or is solidificated in the operating system (operating system, OS) of the terminal device
In software function module.The processor 140 is used to perform the executable module stored in memory 120, such as based on step
The software function module or computer program that the identification authentication system 110 of state identification includes.
Wherein, memory 120 may be, but not limited to, random access memory (Random Access Memory,
RAM), read-only storage (Read Only Memory, ROM), programmable read only memory (Programmable Read-Only
Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM),
Electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only Memory, EEPROM) etc..
Wherein, memory 120 is used for storage program, and the processor 140 performs described program, subsequently after execute instruction is received
The method performed by terminal device that the stream process that any embodiment of the embodiment of the present invention discloses defines can apply to processor
In 140, or realized by processor 140.
Processor 140 is probably a kind of IC chip, has the disposal ability of signal.Above-mentioned processor 140 can
To be general processor, including central processing unit (Central Processing Unit, abbreviation CPU), network processing unit
(Network Processor, abbreviation NP) etc.；Can also be digital signal processor (DSP), application specific integrated circuit (ASIC),
Field programmable gate array (FPGA) either other PLDs, discrete gate or transistor logic, discrete hard
Part component.It can realize or perform disclosed each method, step and the logic diagram in the embodiment of the present invention.General processor
Can be microprocessor or the processor 140 can also be any conventional processor 140 etc..
Various input/output devices are coupled to processor 140 and memory 120 by the Peripheral Interface 150.At some
In embodiment, Peripheral Interface 150, processor 140 and storage control 130 can be realized in one single chip.Other one
In a little examples, they can be realized by independent chip respectively.
Input-output unit 160 is used to be supplied to user input data to realize interacting for user and terminal device.It is described defeated
Enter output unit 160 may be, but not limited to, mouse and keyboard etc..
Audio unit 170 provides a user COBBAIF, and it may include one or more microphones, one or more raises
Sound device and voicefrequency circuit.
Display unit 180 provides an interactive interface (such as user interface) or used between terminal device and user
Referred in display image data to user.In the present embodiment, the display unit 180 can be that liquid crystal display or touch-control show
Show device.If touch control display, it can be the capacitance type touch control screen or resistance type touch control screen for supporting single-point and multi-point touch operation
Deng.Single-point and multi-point touch operation is supported to refer to that touch control display can sense one or more positions on the touch control display
Place is put with caused touch control operation, and the touch control operation that this is sensed transfers to processor 140 to be calculated and handled.
The communication unit 190 is used for by the wireless network and is arranged between the acceleration transducer with user
Connection is established, so as to realize that the terminal device passes through wireless network transceiving data.
Fig. 2 is refer to, is that a kind of flow of identity identifying method based on Gait Recognition provided in an embodiment of the present invention is shown
It is intended to.By this programme provide based on the identity identifying method of Gait Recognition to further increase the accurate of authentication
Degree, this method include：
Step S110, obtain the multiple acceleration informations for the acceleration transducer collection being arranged at user.
The acceleration transducer is arranged at user by being integrated in Wearable, as the Wearable can be with
Be, but be not limited to, mobile phone, bracelet, foot chain etc., then user the Wearable can be worn on by body according to the hobby of oneself
On, such as wrist, arm, chest, waist, thigh.It is readily appreciated that, the acceleration transducer can also be separately set in user's body
On.And then the acceleration transducer being arranged at by this with user gathers multiple acceleration informations in user's walking process,
And LPF is carried out to filter out high-frequency noise using low pass filter to the acceleration information of collection, and more preferably, the low pass filtered
The set of frequency of ripple device is 10HZ.It should be noted that the acceleration transducer can gather three-dimensional acceleration in synchronization
Value, i.e. X, Y, the acceleration magnitude of Z-direction, therefore, the acceleration transducer will be used furtherCalculate
Method is handled the acceleration magnitude of synchronization collection successively, to obtain multiple acceleration informations, wherein, AxFor X-direction
Acceleration magnitude, AzFor the acceleration magnitude of Z-direction, AyFor the acceleration magnitude of Y direction, DusedFor acceleration information.
Step S120, analysis is carried out to the multiple acceleration information and extracts at least one gait cycle.
Because the plurality of acceleration information is gathered respectively for different users, then to multiple acceleration of each user
Degrees of data carries out at least one gait cycle of analysis extraction, the posture walked due to each user, speed, step-length etc. not respectively
Together, then the gait cycle is that unique, different user corresponds to different gait cycles.Fig. 3 is refer to, is the embodiment of the present invention
A kind of schematic flow sheet of the step S120 of the identity identifying method based on Gait Recognition provided sub-step, step S120
Including：
Step S121, calculated according to the multiple acceleration information and estimate step-length.
It is the length that each step of user is stepped out that this, which estimates step-length, and it is this hair that the computational methods for estimating step-length, which refer to Fig. 4,
A kind of schematic flow sheet of the step S121 for identity identifying method based on Gait Recognition that bright embodiment provides sub-step, should
Step S121 includes：
Step S1211, Fourier transformation is carried out to the multiple acceleration information and obtains one sided spectral density function.
Windowing process is carried out to multiple acceleration informations of acquisition, more preferably, the window size is arranged to 8S, window weight
Folded rate is arranged to 0.5, by carrying out windowing process to multiple acceleration informations, to carry out slip segmentation to acceleration, in order to
Fourier transformation is carried out respectively to the acceleration information of every section of adding window, and then Fourier's change is carried out to all acceleration informations
Change.All acceleration informations obtain one sided spectral density function after Fourier transformation, as shown in figure 5, being implementation of the present invention
Example provide a kind of one sided spectral density function schematic diagram, the one sided spectral density function schematic diagram using frequency as abscissa,
Using spectrum energy as ordinate.
Step S1212, cadence is obtained according to the one sided spectral density function.
Frequency corresponding to choosing spectrum energy highest value is cadence, in embodiments of the present invention, by the cadence mark of selection
It is designated as fstep。
Step S1213, calculate the sample frequency of the multiple acceleration.
Due to needing to gather multiple acceleration informations to same user, then the sample frequency of multiple acceleration is calculated, should
Sample frequency is the number of the acceleration information of collection in the unit time, as acquired 100 acceleration informations in 1s.In this hair
In bright embodiment, sample frequency is labeled as fs。
Step S1214, calculated according to the cadence and sample frequency and estimate step-length.
Calculated according to cadence and sample frequency and estimate step-length, specifically, usingAlgorithm calculates and estimates step
It is long, LeTo estimate step-length, fsFor sample frequency, fstepFor cadence.
Step S122, at least one gait cycle is extracted according to the multiple acceleration information and the step-length of estimating.
It is to be analyzed to obtain according to the acceleration information of each user itself due to estimating step-length, therefore, this estimates step-length more
The characteristic of each user can be reflected.In consideration of it, further according to the multiple acceleration information and estimate at least one step of step-length extraction
The state cycle, it is readily appreciated that, gait cycle extracts more, and assay is just more accurate.Fig. 6 is refer to, is of the invention real
A kind of schematic flow sheet of the step S122 of identity identifying method based on Gait Recognition of example offer sub-step, the step are provided
S122 includes：
Step S1221, acceleration information statistical chart, the acceleration information system are made according to the multiple acceleration information
Figure is counted using quantity corresponding to each acceleration as abscissa, using acceleration as ordinate.
Fig. 7 is refer to, is a kind of acceleration information statistical chart provided in an embodiment of the present invention, the acceleration information statistical chart
Drawn according to multiple acceleration informations, it sits using quantity corresponding to each acceleration as abscissa using acceleration to be vertical
Mark.
Step S1222, choose the starting point that first minimum point on the acceleration information statistical chart is gait cycle.
In the acceleration information statistical chart shown in Fig. 7, the starting point that first minimum point is gait cycle is chosen,
In the embodiment of the present invention, the starting point of the gait cycle is labeled as sp.
Step S1223, scope is estimated according to where estimating step-length and starting point determines the terminal of gait cycle.
According to estimating step-length LeDetermine to estimate scope where the terminal of gait cycle with starting point sp, specifically using sp+
Le- d ＜ ep ＜ sp+Le+ d modes, which are determined, estimates scope.Wherein, LeTo estimate step-length, sp is starting point, and ep is gait week
The terminal of phase, d are the deviation for estimating step-length and actual step size.It should be noted that d can pass through d=β Le=0.3 × LeCalculate
Method is determined, wherein LeTo estimate step-length, β is the error for estimating step-length, and in embodiments of the present invention, the β is preferably 0.3.
By being limited to the terminal ep of gait cycle in the range of this estimates so that the correctness and uniqueness of the terminal of gait cycle.
Step S1224, estimate described in selection in the range of minimum point be gait cycle terminal.
The terminal that the minimum point in the range of estimating is gait cycle is chosen in the acceleration information statistical chart shown in Fig. 7
ep.Step S1222~step 1224 has simply exemplarily enumerated the determination method of first gait cycle, it is readily appreciated that,
Other gait cycles are also determined using same method, are such as chosen first after the terminal ep of current gait cycle minimum
Value point is the starting point of next gait cycle, then uses the same terminal estimated range determining method and determine gait cycle
The terminal estimated scope and then determine gait cycle, final extraction obtains multiple gait cycles.
Step S130, each gait cycle is normalized using cubic spline interpolation, so that the step
The length in state cycle is consistent with the length of default gait cycle template.
If extraction obtains N number of gait cycle, cubic spline interpolation is respectively adopted to N number of gait cycle length is carried out
Normalized, in inventive embodiments, the length of the gait cycle after being each normalized is 200, it is readily appreciated that
, the length of the gait cycle can be configured according to being actually needed.The normalized result HcyclesFor：
A gait cycle after each behavior normalization in the formula.By carrying out normalizing to each gait cycle
Change processing and make it that the length of gait cycle is consistent with the length of default gait cycle template, in embodiments of the present invention, the gait
The length of the length in cycle and default gait cycle template is 200.
Step S140, calculate at least one gait cycle and the matching degree average of default gait cycle template.
In embodiments of the present invention, the default gait cycle template is analyzed for the acceleration information of collection user in advance
After establish, the method for building up of the default gait cycle template is identical with the extracting method of gait cycle.The default gait cycle mould
The process of establishing of plate is：The multiple history acceleration informations for the acceleration transducer collection being arranged at user are obtained in advance,
Multiple history acceleration informations are calculated and estimate step-length, according to multiple history acceleration informations and estimate first step of step-length extraction
State cycle, the method that first gait cycle of step-length and extraction is estimated in its calculating have been previously stated, are not repeated herein.
After extracting first gait cycle, first gait cycle is walked using cubic spline interpolation to this first
The length in state cycle is normalized, and the length of first gait cycle after normalized is 200, and then will be through
First gait cycle after normalized saves as the default gait cycle template that can characterize the user identity, i.e. Ttemp
=spline (Tcycle), wherein, TtempFor default gait cycle template, TcycleFor first gait week after normalized
Phase.
It should be noted that when establishing default gait cycle template, multiple history acceleration informations of user are divided
First gait cycle is only extracted after analysis, default gait cycle template is obtained after handling first gait cycle.It
So when establishing default gait cycle template, only extract first gait cycle or arbitrarily one gait cycle of extraction, be because
Can quickly to establish template.Simultaneously as in practical application, acquire the multiple acceleration informations of user, and to multiple
Acceleration information analysis after be extracted multiple gait cycles, then respectively by each gait cycle with default gait cycle mould
Plate is matched so that during practical application, has higher accuracy.It is readily appreciated that, the default gait cycle template also may be used
Multiple gait cycles are extracted after analyzing multiple history acceleration informations, and then are established according to multiple gait cycles, it is such as right
Multiple gait cycles form default gait cycle template etc. after taking average.
It calculates at least one gait cycle and the specific implementation side of the matching degree average of default gait cycle template
Formula is：Each gait cycle is subjected to Pearson correlation coefficient calculating with default gait cycle template respectively, especially byAlgorithm realizes,For one of gait cycle and default gait week
The Pearson correlation coefficient of phase template.Then, the Pearson came phase relation of all gait cycles and default gait cycle template is calculated
Several averages, especially byAlgorithm realization, MscoreFor all gait cycles and default gait cycle
The average of the Pearson correlation coefficient of template, the average are the matching of at least one gait cycle and default gait cycle template
Spend average.
Step S150, if the matching degree average is more than predetermined threshold value, pass through authentication.
Further analysis is set the predetermined threshold value in default gait cycle template, and the predetermined threshold value takes into full account different use
The otherness at family is configured, and then more accurate by predetermined threshold value progress authentication.The set-up mode of the predetermined threshold value
For：The history acceleration information Dused={ xi, i=1,2 ... L } gathered in advance is divided into two parts, a part is for dividing
Analyse first gait cycle, i.e., the history acceleration information of default gait cycle template, be characterized as Tcycle=xi, i=sp,
Sp+1 ... ep }, another part be all history acceleration informations remove for presetting gait cycle template part other add
Speed data, it is characterized as Drest={ xj, j=ep+1, ep+2 ... ... L }.Drest is divided into the data isometric with Tcycle
Collection, that is, the length for assuming Tcycle is s=ep-sp+1, and Drest is divided into the data set Ds (k) that k length is s, the Ds
(k) it is expressed as Ds(k)=[Drest(k) ... Drest(k+s)], k=1,2,3......R.And then calculate Tcycle and each Ds
(k) Pearson correlation coefficient ρ (k), the ρ (k) algorithm is：ρ (k)=PCC (Tcycle, Ds(k)), k=1.2 ... .R.Finally
Pass through algorithmCalculate predetermined threshold value Th.
If the matching degree average is more than predetermined threshold value, the user of current authentication and the user profile of prior typing are proved
It is high with degree, then authenticating user identification success.
As can be seen here, default gait cycle template and predetermined threshold value are set in advance by this programme, in actual use,
The multiple gait cycles of analysis acquisition are carried out to the acceleration information of the user of collection, further according to the acquisition of multiple gait cycles
After degree average, directly compared with predetermined threshold value, quickly to draw a conclusion.It should be noted that due to nothing in this programme
By the foundation for being default gait cycle template or the acceleration information analysis to user obtains gait cycle in real time, is basis
Established after the step-length of itself analysis of each user, taken into full account the individual difference of each user；In addition, predetermined threshold value is set
Put and be configured after analyzing in advance a large amount of acceleration informations of user, the predetermined threshold value of each user not phase
Together.Therefore, gait cycle and predetermined threshold value are set after individual difference of this programme by taking into full account each user, with very big
Ground improves the accuracy rate of the authentication based on Gait Recognition.
In order to be better described a kind of identity identifying method based on Gait Recognition provided in an embodiment of the present invention have compared with
The higher accuracy rate of in general gait recognition method, below by way of a description of test.It is specific as follows：
Experimenter is allowed to put on the sport health shirt with acceleration transducer of development in laboratory, on the sport health shirt
The acceleration transducer of setting is located at the chest locations of experimenter, and the sample frequency of the acceleration transducer is 100HZ, sampling
Precision is 16.
Three experimenters are allowed to wear respectively on the sport health shirt, each experimenter is with leg speed 2Km/h-6Km/h and big
The amplitude for showing 0.5Km/h is incremented by.To each experimenter, everyone gathers 6 groups of data every time, and every group of data include 500 gaits
In the cycle, twice, the time interval of data acquisition twice is 15 days for collection altogether.
The analysis of two aspects is carried out to the data of collection, is specially：
In a first aspect, the accuracy rate of gait cycle extraction is detected, especially byAlgorithm realization, wherein, NcyclesFor reality gait cycle number, in embodiments of the present invention,
It is arranged to 500；NdetectedWhat the identity identifying method based on Gait Recognition to be used when actually carrying out authentication extracted
Gait cycle number；R is testing time, is 36 in embodiments of the present invention.Calculated by the gait cycle number to reality and method
The analysis of gait cycle number obtain the schematic diagram of gait cycle Detection accuracy as shown in Figure 8, as seen from the figure, pass through algorithm
The gait cycle accuracy rate extracted is high.
Second aspect, identification accuracy rate is detected, especially byAlgorithm realization, wherein, Nii
To identify correct number, NiotherFor the number of misrecognition.In embodiments of the present invention, pass throughCalculate 3
The identification accuracy rate of experimenter, the schematic diagram of identification accuracy rate as shown in Figure 9, as seen from the figure, passes through we
Method is that identification accuracy rate is high, is approximately higher than the 5.7% of existing gait recognition method.Therefore, provided by this programme
A kind of identity identifying method based on Gait Recognition can be greatly enhanced the accuracy rate of authentication.
Figure 10 is refer to, is a kind of work(of identification authentication system 110 based on Gait Recognition provided in an embodiment of the present invention
Energy module diagram, being somebody's turn to do the identification authentication system 110 based on Gait Recognition includes acquisition module 111, analysis module 112, processing
Module 113, computing module 114 and comparison module 115, wherein,
Acquisition module 111, for obtaining multiple acceleration informations of the acceleration transducer being arranged at user collection.
In embodiments of the present invention, step S110 can be performed by acquisition module 111.
Analysis module 112, at least one gait cycle is extracted for carrying out analysis to the multiple acceleration information.
In embodiments of the present invention, step S120~S1223 can be performed by analysis module 112.
Processing module 113, for each gait cycle to be normalized using cubic spline interpolation, so that
The length of the gait cycle is consistent with the length of default gait cycle template.
In embodiments of the present invention, step S130 can be performed by processing module 113.
Computing module 114, it is equal for calculating at least one gait cycle and the matching degree of default gait cycle template
Value.
In embodiments of the present invention, step S140 can be performed by computing module 114.
Comparison module 115, if being more than predetermined threshold value for the matching degree average, pass through authentication.
In embodiments of the present invention, step S150 can be performed by comparison module 115.
Due to being had been described in the identity identifying method part based on Gait Recognition, will not be repeated here.
The embodiment of the present invention further discloses a kind of computer-readable recording medium, is stored thereon with computer program, described
Computer program realizes the authentication side based on Gait Recognition that the foregoing embodiment of the present invention discloses when being performed by processor 140
Method.
In summary, a kind of identity identifying method and device based on Gait Recognition provided in an embodiment of the present invention, the party
Method includes：The multiple acceleration informations for the acceleration transducer collection being arranged at user are obtained, to the multiple acceleration
Sensing data carries out analysis and extracts at least one gait cycle, calculates at least one gait cycle and default gait cycle
The matching degree average of template, if matching degree average is more than predetermined threshold value, pass through authentication.This programme is by gathering user's row
Multiple acceleration informations during walking, and gait cycle is extracted after analyzing the plurality of acceleration information, with further
Each gait cycle is matched with default gait cycle template.Due to being to gather multiple add respectively for different users
Speed data simultaneously calculates gait cycle, therefore, preferably meets the individual difference of different user, improves and is known based on gait
The degree of accuracy of other authentication.
In several embodiments provided herein, it should be understood that disclosed apparatus and method, can also pass through
Other modes are realized.Device embodiment described above is only schematical, for example, flow chart and block diagram in accompanying drawing
Show the device of multiple embodiments according to the present invention, method and computer program product architectural framework in the cards,
Function and operation.At this point, each square frame in flow chart or block diagram can represent the one of a module, program segment or code
Part, a part for the module, program segment or code include one or more and are used to realize holding for defined logic function
Row instruction.It should also be noted that at some as in the implementation replaced, the function that is marked in square frame can also with different from
The order marked in accompanying drawing occurs.For example, two continuous square frames can essentially perform substantially in parallel, they are sometimes
It can perform in the opposite order, this is depending on involved function.It is it is also noted that every in block diagram and/or flow chart
The combination of individual square frame and block diagram and/or the square frame in flow chart, function or the special base of action as defined in performing can be used
Realize, or can be realized with the combination of specialized hardware and computer instruction in the system of hardware.
In addition, each functional module in each embodiment of the present invention can integrate to form an independent portion
Point or modules individualism, can also two or more modules be integrated to form an independent part.
If the function is realized in the form of software function module and is used as independent production marketing or in use, can be with
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially in other words
The part to be contributed to prior art or the part of the technical scheme can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, including some instructions are causing a computer equipment (can be
People's computer, server, or network equipment etc.) perform all or part of step of each embodiment methods described of the present invention.
It should be noted that herein, such as first and second or the like relational terms are used merely to an entity or behaviour
Make with another entity or operation make a distinction, and not necessarily require or imply these entities or operate between exist it is any this
Kind actual relation or order.Moreover, term " comprising ", "comprising" or its any other variant are intended to nonexcludability
Include so that process, method, article or equipment including a series of elements not only include those key elements, but also
Including the other element being not expressly set out, or also include for this process, method, article or equipment intrinsic want
Element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that wanted including described
Other identical element also be present in the process of element, method, article or equipment.
The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.Within the spirit and principles of the invention, that is made any repaiies
Change, equivalent substitution, improvement etc., should be included in the scope of the protection.It should be noted that：Similar label and letter exists
Similar terms is represented in following accompanying drawing, therefore, once being defined in a certain Xiang Yi accompanying drawing, is then not required in subsequent accompanying drawing
It is further defined and explained.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all be contained
Cover within protection scope of the present invention.Therefore, protection scope of the present invention described should be defined by scope of the claims.
Claims (10)
1. a kind of identity identifying method based on Gait Recognition, it is characterised in that methods described includes：
Obtain the multiple acceleration informations for the acceleration transducer collection being arranged at user；
Analysis is carried out to the multiple acceleration information and extracts at least one gait cycle；
Calculate the matching degree average of at least one gait cycle and default gait cycle template；
If the matching degree average is more than predetermined threshold value, pass through authentication.
2. the identity identifying method based on Gait Recognition as claimed in claim 1, it is characterised in that described to add to the multiple
Speed data include the step of analyzing extraction at least one gait cycle：
Calculated according to the multiple acceleration information and estimate step-length；
At least one gait cycle is extracted according to the multiple acceleration information and the step-length of estimating.
3. the identity identifying method based on Gait Recognition as claimed in claim 2, it is characterised in that described according to the multiple
Acceleration information, which calculates the step of estimating step-length, to be included：
Fourier transformation is carried out to the multiple acceleration information and obtains one sided spectral density function；
Cadence is obtained according to the one sided spectral density function；
Calculate the sample frequency of the multiple acceleration；
Calculated according to the cadence and sample frequency and estimate step-length.
4. the identity identifying method based on Gait Recognition as claimed in claim 2, it is characterised in that described according to the multiple
Acceleration information and described the step of estimating step-length extraction at least one gait cycle, include：
Acceleration information statistical chart is made according to the multiple acceleration information, the acceleration statistical chart is with each acceleration
Corresponding quantity is abscissa, using acceleration as ordinate；
Choose the starting point that first minimum point on the acceleration information statistical chart is gait cycle；
Scope is estimated according to where estimating step-length and starting point determines the terminal of gait cycle；
Minimum point in the range of being estimated described in selection is the terminal of gait cycle.
5. the identity identifying method based on Gait Recognition as claimed in claim 1, it is characterised in that described in the calculating at least
The step of one gait cycle and the matching degree average of default gait cycle template, includes：
Calculate each gait cycle and the Pearson correlation coefficient of default gait cycle template；
The average of all Pearson correlation coefficients is calculated, the average of the Pearson correlation coefficient is at least one step
State cycle and the matching degree average of default gait cycle template.
6. the identity identifying method based on Gait Recognition as claimed in claim 1, it is characterised in that described to add to the multiple
Speed data carries out also including step after at least one gait cycle is extracted in analysis：
Each gait cycle is normalized using cubic spline interpolation so that the length of the gait cycle with
The length of default gait cycle template is consistent.
7. the identity identifying method based on Gait Recognition as claimed in claim 1, it is characterised in that the default gait cycle
Template is arranged at multiple history acceleration informations of the acceleration transducer collection of user to obtain in advance, with according to described more
First gait cycle being determined after the analysis of individual history acceleration information and establish, the multiple history acceleration information is analyzed
One sided spectral density function is obtained including carrying out Fourier transformation to the multiple history acceleration information, according to the unilateral frequency
The cadence and sample frequency that spectral density function obtains, which calculate, estimates step-length, and first gait cycle is determined according to step-length is estimated, and
First gait cycle is normalized.
8. the identity identifying method based on Gait Recognition as claimed in claim 7, it is characterised in that the predetermined threshold value passes through
Other history acceleration informations in the multiple history acceleration information in addition to first gait cycle are divided into multiple
The data set of predetermined length, the Pearson correlation coefficient of each data set and default gait cycle template is calculated, and according to multiple
Pearson correlation coefficient is calculated.
9. a kind of identification authentication system based on Gait Recognition, it is characterised in that described device includes：
Acquisition module, for obtaining multiple acceleration informations of the acceleration transducer being arranged at user collection；
Analysis module, at least one gait cycle is extracted for carrying out analysis to the multiple acceleration information；
Computing module, for calculating the matching degree average of at least one gait cycle and default gait cycle template；
Comparison module, if being more than predetermined threshold value for the matching degree average, pass through authentication.
10. the identification authentication system based on Gait Recognition as claimed in claim 9, it is characterised in that described device also includes：
Processing module, for each gait cycle to be normalized using cubic spline interpolation, so that the step
The length in state cycle is consistent with the length of default gait cycle template.
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| CN201711286270.3A CN107831907A (en) | 2017-12-07 | 2017-12-07 | Identity identifying method and device based on Gait Recognition |
| PCT/CN2017/120107 WO2019109433A1 (en) | 2017-12-07 | 2017-12-29 | Identity authentication method and device based on gait recognition |
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| CN108596100A (en) * | 2018-04-25 | 2018-09-28 | 常州大学 | A kind of personal identification method based under multi-pose |
| CN108932504A (en) * | 2018-07-24 | 2018-12-04 | 中国科学院深圳先进技术研究院 | Identity identifying method, device, electronic equipment and storage medium |
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| CN108563939A (en) * | 2018-04-25 | 2018-09-21 | 常州大学 | Human body identification based on gait geometric locus feature |
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