CN109636397A - Transit trip control method, device, computer equipment and storage medium - Google Patents
Transit trip control method, device, computer equipment and storage medium Download PDFInfo
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- G06Q20/401—Transaction verification
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- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
- G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
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Abstract
The present invention discloses a kind of transit trip control method, device, computer equipment and storage medium, comprising: obtains the facial image of the one or more passengers entered in public transport compass of competency, facial image includes facial contour feature；Facial image is matched in the preset database, includes facial image collected and the set with the identity information of the facial image phase mapping and account information in presetting database；Whether detection facial image meets preset condition, allows current when meeting preset condition and pays transportation expenses from facial image mapped account information.Whole process is simple, convenient, can read multiple people simultaneously, accelerate recognition speed and the passage speed of passenger, save riding time, automatic to pay, and keeps passenger more convenient by bus.Identity information by obtaining passenger avoids criminal from being mixed into public transport place and stages an armed rebellion, improve the supervision of the safe order of public transport in order to be monitored to passenger.
Description
Technical field
The present invention relates to computer application technologies, specifically, the present invention relates to a kind of transit trip controls
Method, apparatus, computer equipment and storage medium.
Background technique
Public transport, subway trip are the mode of most people trip, and the recommendation trip mode as low-carbon trip.It is public
Often flow of the people is very big for the public transport such as friendship, subway, entered the station and payment process in require to be lined up.
The security monitoring in public transport is only checked personal luggage by rays safety detection apparatus at present, as long as not taking
Personnel with some violated products such as controlled knife can take public transport, and therefore, some criminals can take advantage of the occasion
It commits theft in these public transport, part passenger is caused to sustain a loss, station employees can not manage these personnel.
In addition it in the payment process for carrying out public transport, needs passenger to be lined up one by one and swipes the card or pay in cash,
The time of cost is long, low efficiency, and special employee is needed to be managed, and human cost expenditure is big.
Summary of the invention
The purpose of the present invention is intended at least can solve above-mentioned one of technological deficiency, open one kind can rapid payment, peace
Transit trip control method go on a journey entirely and supervision, device, computer equipment and storage medium.
In order to achieve the above object, the present invention discloses a kind of transit trip control method, comprising:
The facial image of the one or more passengers entered in public transport compass of competency is obtained, the facial image includes
Facial contour feature；
Match the facial image in the preset database, include facial image collected in the presetting database with
And the set with the identity information of the facial image phase mapping and account information；
It detects whether the facial image meets preset condition, allows when meeting preset condition current and from the face
Transportation expenses are paid in image mapped account information.
Further, the side of the facial image for obtaining the one or more passengers entered in public transport compass of competency
Method includes:
Video image in captured public transport compass of competency is input in neural network model；
Identify one or more portraits in the video image；
In vivo detection is carried out to extract corresponding facial contour feature to each portrait.
Further, each passenger's acquisition has the facial image of multiple angles to store in the database, described pre-
If the method for matching the facial image in database includes:
The facial image of identification is matched with the angled facial image of institute in presetting database；
It chooses matching degree and is greater than or equal to the facial image of preset threshold as target facial image；
Obtain target facial image mapped identity information and account information.
Further, described to choose facial image of the matching degree more than or equal to preset threshold as target facial image
Before, further includes:
Judge whether matching degree is greater than 1 more than or equal to the quantity of the facial image of preset threshold；
When quantity is greater than 1, obtains the facial image of the passenger another angle and match.
Further, it is legal identity information that the preset condition, which includes the identity information of the facial image mapping,.
Further, the preset condition includes that the remaining sum in the account information of the facial image mapping is greater than or equal to
Threshold value or the remaining sum of at least one and the interlock account of the account information are greater than or equal to threshold value.
Further, the identity information further includes that passenger communicates account, further includes:
Public transport information is sent to the communications account or account information changes notice.
On the other hand, the application discloses a kind of transit trip control device, comprising:
It obtains module: being configured as executing the face for obtaining the one or more passengers entered in public transport compass of competency
Image, the facial image include facial contour feature；
Processing module: being configured as executing and match the facial image in the preset database, in the presetting database
Set including facial image collected and with the identity information of the facial image phase mapping and account information；
Execution module: being configured as executing and detect whether the facial image meets preset condition, when meeting preset condition
When allow current and pay transportation expenses from the facial image mapped account information.
Further, further includes:
Input module: it is configured as executing the video image in captured public transport compass of competency is input to nerve
In network model；
Identification module: it is configured as executing the one or more portraits identified in the video image；
Extraction module: it is configured as executing to each portrait progress In vivo detection to extract corresponding facial contour feature.
Further, each passenger's acquisition has the facial image storage of multiple angles in the database, further includes:
First matching module: it is configured as executing the angled people of institute in the facial image and presetting database by identification
Face image is matched；
Object selection module: it is configured as executing and chooses facial image of the matching degree more than or equal to preset threshold as mesh
Mark facial image；
Identity obtains module: being configured as executing acquisition target facial image mapped identity information and account information.
Further, further includes:
Judgment module: be configured as execute judge matching degree more than or equal to preset threshold facial image quantity whether
Greater than 1；
Second matching module: it is configured as executing when quantity is greater than 1, obtains the facial image of another angle of the passenger
And it is matched.
Further, it is legal identity information that the preset condition, which includes the identity information of the facial image mapping,.
Further, the preset condition includes that the remaining sum in the account information of the facial image mapping is greater than or equal to
Threshold value or the remaining sum of at least one and the interlock account of the account information are greater than or equal to threshold value.
Further, the identity information further includes that passenger communicates account, further includes:
Information sending module: it is configured as executing to communications account transmission public transport information or account information variation
Notice.
Another aspect the application discloses a kind of computer equipment, including memory and processor, stores in the memory
There is computer-readable instruction, when the computer-readable instruction is executed by the processor, so that the processor executes as above
The step of stating described in any item transit trip control methods.
A kind of storage medium for being stored with computer-readable instruction is also disclosed in another aspect the application, described computer-readable
When instruction is executed by one or more processors, so that one or more processors execute public friendship as described in any one of the above embodiments
The step of pass-out row control method.
The beneficial effects of the present invention are:
The application discloses a kind of transit trip control method, enters public transport administrative area by photographic device shooting
Image in domain, obtains the facial image of one or more passengers, while identifying to multiple facial images, obtains its identity
Information and account information allow its passage when identity information and account information all meet preset condition, and believe automatically from account
Corresponding expense is deducted in breath, whole process is simple, convenient, can read multiple people simultaneously, accelerates recognition speed and passenger
Passage speed saves riding time, automatic to pay, and keeps passenger more convenient by bus.By obtaining the identity information of passenger, so as to
It is monitored in passenger, avoids criminal from being mixed into public transport place and stage an armed rebellion, improve the prison of the safe order of public transport
Pipe dynamics.
The additional aspect of the present invention and advantage will be set forth in part in the description, these will become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Above-mentioned and/or additional aspect and advantage of the invention will become from the following description of the accompanying drawings of embodiments
Obviously and it is readily appreciated that, in which:
Fig. 1 is transit trip control method flow chart of the present invention；
Fig. 2 is the method flow diagram that the present invention obtains facial image；
Fig. 3 is the training method flow chart of convolutional neural networks model of the present invention；
Fig. 4 is the method flow diagram that the present invention matches facial image in the preset database；
Fig. 5 is the step flow chart of the invention obtained before target facial image；
Fig. 6 is transit trip control method device block diagram of the present invention；
Fig. 7 is computer equipment basic structure block diagram of the present invention.
Specific embodiment
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, and for explaining only the invention, and is not construed as limiting the claims.
Those skilled in the art of the present technique are appreciated that unless expressly stated, singular " one " used herein, " one
It is a ", " described " and "the" may also comprise plural form.It is to be further understood that being arranged used in specification of the invention
Diction " comprising " refer to that there are the feature, integer, step, operation, element and/or component, but it is not excluded that in the presence of or addition
Other one or more features, integer, step, operation, element, component and/or their group.It should be understood that when we claim member
Part is " connected " or when " coupled " to another element, it can be directly connected or coupled to other elements, or there may also be
Intermediary element.In addition, " connection " used herein or " coupling " may include being wirelessly connected or wirelessly coupling.It is used herein to arrange
Diction "and/or" includes one or more associated wholes for listing item or any cell and all combinations.
Those skilled in the art of the present technique are appreciated that unless otherwise defined, all terms used herein (including technology art
Language and scientific term), there is meaning identical with the general understanding of those of ordinary skill in fields of the present invention.Should also
Understand, those terms such as defined in the general dictionary, it should be understood that have in the context of the prior art
The consistent meaning of meaning, and unless idealization or meaning too formal otherwise will not be used by specific definitions as here
To explain.
Those skilled in the art of the present technique are appreciated that " terminal " used herein above, " terminal device " both include wireless communication
The equipment of number receiver, only has the equipment of the wireless signal receiver of non-emissive ability, and including receiving and emitting hardware
Equipment, have on bidirectional communication link, can execute two-way communication reception and emit hardware equipment.This equipment
It may include: honeycomb or other communication equipments, shown with single line display or multi-line display or without multi-line
The honeycomb of device or other communication equipments；PCS (Personal Communications Service, PCS Personal Communications System), can
With combine voice, data processing, fax and/or communication ability；PDA (Personal Digital Assistant, it is personal
Digital assistants), it may include radio frequency receiver, pager, the Internet/intranet access, web browser, notepad, day
It goes through and/or GPS (Global Positioning System, global positioning system) receiver；Conventional laptop and/or palm
Type computer or other equipment, have and/or the conventional laptop including radio frequency receiver and/or palmtop computer or its
His equipment." terminal " used herein above, " terminal device " can be it is portable, can transport, be mounted on the vehicles (aviation,
Sea-freight and/or land) in, or be suitable for and/or be configured in local runtime, and/or with distribution form, operate in the earth
And/or any other position operation in space." terminal " used herein above, " terminal device " can also be communication terminal, on
Network termination, music/video playback terminal, such as can be PDA, MID (Mobile Internet Device, mobile Internet
Equipment) and/or mobile phone with music/video playing function, it is also possible to the equipment such as smart television, set-top box.
Specifically, being suitble to quick trip, wisdom referring to Fig. 1, the present invention discloses a kind of transit trip control method
Trip, referring specifically to Fig. 1, transit trip control method includes:
S1000, the facial image for obtaining the one or more passengers entered in public transport compass of competency, the face figure
As including facial contour feature；
The vehicles and produce institute, such as bus, subway, high-speed rail, train, taxi that public transport traffic is gone on a journey for convenience of people
Vehicle etc. after public transport compass of competency fingering here enters public transport compass of competency, and needs to carry out to seating public transport
The range areas that tool is paid, for example for bus and taxi, compass of competency is to climb up bus or taxi
Car, the facial image that such situation obtains passenger can be obtained by being located at the camera in bus or in taxi.
For subway, high-speed rail and train, the region by bus that public transport compass of competency can either set for security inspection area, such as
The gate regional scope that enters the station and outbound gate regional scope, the facial image of passenger can be entered the station or outbound by being mounted at this time
The monitoring camera in gate region obtains.It should be noted that either which kind of vehicles, photographic device should be all mounted on
It can understand and can take the position of the positive face of passenger.
It is subway, in case where high-speed rail and train by the public transport vehicles, the installation method of photographic device is to be mounted on
Gate mouth position, when passenger passes through gate mouth, face is towards photographic device, the positive face of taken of passengers.In such cases, passenger
It is one by one by gate.
In another embodiment, the mountable each position in gate mouth of photographic device, in order to from each different side
To the image information for obtaining passenger, the image information of each different directions is associated, the facial image and lock of passenger are obtained
Determine the specific location and movement tendency of passenger, in this way, can obtain passenger will be entered by which gate mouth,
If passenger meets the condition for taking public transport, when passenger enters gate mouth region domain, clearance passes through, when passenger does not meet seating
The condition of public transport, when the passenger enters gate mouth region domain, gate lockjaw is stopped it and is passed through.Such mode can once obtain more
The facial image and location information of a passenger.
Since the patronage for taking public transport is all more, and enter the passengers quantity of public transport compass of competency simultaneously
It may also be to be multiple, in one embodiment, referring to Fig. 2, described obtain one or more entered in public transport compass of competency
The method of the facial image of a passenger includes:
S1100, the video image in captured public transport compass of competency is input in neural network model；
In order to quick obtaining image information, photographic device shoots dynamic video image to input neural network mould
The key frame picture with the positive face of passenger is chosen in type and is identified.It should be noted that being carried out in input neural network model
The picture of the shooting of photographic device again for being also possible to select of identification has the image of positive face, or chooses from video
The key frame picture with positive face.
Neural network herein refers to artificial neural network, with self-learning function.Such as when realizing image recognition, only
It needs that many different image templates and the corresponding result that should be identified first are inputted artificial neural network, network will be by certainly
Learning functionality, slowly association identifies similar image.Self-learning function has especially important meaning for prediction.It is expected that following
Artificial neural network computer will provide economic forecasting, market prediction, effectiveness forecasting for the mankind, be far big using future
's.In addition, it has the function of connection entropy.The feedback network of employment artificial neural networks can realize this association.Also have
High speed finds the ability of optimization solution.The optimization solution for finding a challenge, generally requires very big calculation amount, utilizes a needle
The feedback-type artificial neural network designed certain problem, plays the high-speed computation ability of computer, may find optimization quickly
Solution.Based on a little, the application identifies human body head portrait information using trained neural network model above.
Neural network includes deep neural network, convolutional neural networks, Recognition with Recurrent Neural Network, depth residual error network etc., sheet
Application is illustrated by taking convolutional neural networks as an example, and convolutional neural networks are a kind of feedforward neural networks, and artificial neuron can be with
Surrounding cells are responded, large-scale image procossing can be carried out.Convolutional neural networks include convolutional layer and pond layer.Convolutional neural networks
(CNN) purpose of convolution is to extract certain features from image in.The basic structure of convolutional neural networks includes two
Layer, one are characterized extract layer, and the input of each neuron is connected with the local acceptance region of preceding layer, and extracts the spy of the part
Sign.After the local feature is extracted, its positional relationship between other feature is also decided therewith；The second is feature is reflected
Layer is penetrated, each computation layer of network is made of multiple Feature Mappings, and each Feature Mapping is a plane, all nerves in plane
The weight of member is equal.Activation primitive of the Feature Mapping structure using the small sigmoid function of influence function core as convolutional network,
So that Feature Mapping has shift invariant.Further, since the neuron on a mapping face shares weight, thus reduce net
The number of network free parameter.Each of convolutional neural networks convolutional layer all followed by one be used to ask local average with it is secondary
The computation layer of extraction, this distinctive structure of feature extraction twice reduce feature resolution.
Convolutional neural networks are mainly used to the X-Y scheme of identification displacement, scaling and other forms distortion invariance.Due to
The feature detection layer of convolutional neural networks is learnt by training data, so avoiding when using convolutional neural networks
Explicit feature extraction, and implicitly learnt from training data；Furthermore due to the neuron on same Feature Mapping face
Weight is identical, so network can be with collateral learning, this is also convolutional network is connected with each other the one big excellent of network relative to neuron
Gesture.
The storage form of one width color image in a computer is a three-dimensional matrix, and three dimensions are image respectively
Wide, Gao He RGB (RGB color-values) value, and the storage form of a width gray level image in a computer is a two-dimensional matrix,
Two dimensions are the width of image, height respectively.The either two-dimensional matrix of the three-dimensional matrice of color image or gray level image, matrix
In each element value range be [0,255], but meaning is different, and the three-dimensional matrice of color image can split into R, G, B
Three two-dimensional matrixes, the element in matrix respectively represent R, G, B brightness of image corresponding position.The two-dimensional matrix of gray level image
In, the gray value of element then representative image corresponding position.And bianry image can be considered a simplification of gray level image, it is by gray scale
All original transformations higher than some threshold value are 1 in image, are otherwise 0, therefore the element in bianry image matrix non-zero then 1, two-value
Image is enough to describe the profile of image, and an important function of two convolution operations is exactly to find the edge contour of image.
By converting images into bianry image, then pass through the edge feature that image object is obtained by filtration of convolution kernel, then
The dimensionality reduction of image is realized by pondization in order to obtain, it will be apparent that characteristics of image.By model training, to identify described image
Middle characteristics of image.
One or more portraits in S1200, the identification video image；
The neural network model mentioned in S1100 through the above steps, can identify simultaneously one in video image or
Multiple portraits, in the application, portrait can be obtained as a feature in captured image by convolutional neural networks training
Neural network model obtain, however, it is also possible to using other neural networks, for example DNN (deep-neural-network), RNN (are followed
Ring neural network) etc. network models training form.No matter which kind of neural network is trained, using the mode of this machine learning
It is almost the same come the principle that obtains the method for portrait.
By taking the training method of convolutional neural networks model as an example, referring to Fig. 3, the training method of convolutional neural networks model
It is as follows:
S1110, acquisition are marked with the training sample data that classification judges information；
Training sample data are the component units of entire training set, and training set is by several training sample training data groups
At.Training sample data are believed by the data of a variety of different objects and to the classification judgement that various different objects are marked
Breath composition.Classification judges that information refers to that people according to the training direction of input convolutional neural networks model, pass through universality
The artificial judgement that judgment criteria and true state make training sample data, that is, people are to convolutional neural networks model
The expectation target of output numerical value.Such as, in a training sample data, manual identified go out object in the image information data with
Object in pre-stored image information be it is same, then demarcate the object classification judge information for pre-stored target object
Image is identical.
S1120, the mould that training sample data input convolutional neural networks model is obtained to the training sample data
Type classification is referring to information；
Training sample set is sequentially inputted in convolutional neural networks model, and obtains convolutional neural networks model inverse
The category of model of one full articulamentum output is referring to information.
Category of model referring to the excited data that information is that convolutional neural networks model is exported according to the subject image of input,
It is not trained to before convergence in convolutional neural networks model, classification is the biggish numerical value of discreteness referring to information, when convolution mind
It is not trained to convergence through network model, classification is metastable data referring to information.
S1130, by stop loss function ratio to the categories of model of samples different in the training sample data referring to information with
The classification judges whether information is consistent；
Stopping loss function is judged referring to information with desired classification for detecting category of model in convolutional neural networks model
The whether consistent detection function of information.When the output result of convolutional neural networks model and classification judge the expectation of information
As a result it when inconsistent, needs to be corrected the weight in convolutional neural networks model, so that convolutional neural networks model is defeated
Result judges that the expected result of information is identical with classification out.
S1140, when the category of model judges that information is inconsistent referring to information and the classification, iterative cycles iteration
The weight in the convolutional neural networks model is updated, until the comparison result terminates when judging that information is consistent with the classification.
When the output result of convolutional neural networks model and classification judge information expected result it is inconsistent when, need to volume
Weight in product neural network model is corrected, so that the output result of convolutional neural networks model and classification judge information
Expected result is identical.
S1300, In vivo detection is carried out to each portrait to extract corresponding facial contour feature.
Further, it can not only be incited somebody to action from the video or picture in inputted neural network model using neural network model
The object identification of portrait and surrounding comes out, moreover it is possible to by identifying that the facial contour feature of different portraits identifies different people
Come, know otherwise, only training sample is different, when needing to identify face, can select with several different peoples
The picture of face is as training sample.Since different faces contouring, the colour of skin, face ratio and size are different, lead to
Whether cross and identify that these information may recognize that is the same person.
In one embodiment, a kind of it might be that in captured image, it is understood that there may be some billboards or
Person needs to carry out the portrait identified as beautiful, traffic guiding purpose portrait simulation model in order to distinguish it with true man
In vivo detection, in the application, 3D face In vivo detection is can be used in the method for In vivo detection, and the method for detection includes:
1) three-dimensional information of 256 characteristic points of living body and non-living body human face region is extracted from the image of input, and
The analysis processing in first portion has been carried out to the geometric relationship between these points；
2) three-dimensional information of entire human face region is extracted, and is handled corresponding characteristic point is further, then using association
The method for adjusting training Co-training has trained positive and negative sample data, has carried out first classification using obtained classifier later；
3) fitting of curved surface is carried out to describe threedimensional model feature, then using the extracted characteristic point of two above step
Elevated regions are extracted from depth image according to the curvature of curved surface, then to each extracted region EGI feature, it is finally spherical using it
The degree of correlation carries out Classification and Identification again.
S2000, the facial image is matched in the preset database, include face collected in the presetting database
Image and set with the identity information of the facial image phase mapping and account information；
Presetting database is the database in order to which face and account to be connected to foundation, including facial image, face figure
As the identity information and account information of mapping.Wherein the facial image needs in presetting database are acquired in advance, this is in advance
Acquisition can be to be acquired when passenger handles transportation card, in this way can be simultaneously by facial image, identity information and account information
It associates together, is also possible to the facial image obtained from public security system and matching identity information, as long as will
Corresponding account information associates.
Further, when carrying out human image collecting, the face of multiple angles can be acquired to everyone, such as just
The side face of face and the right and left is further, correct in order to improve in order to compare when recognition of face from multiple angles
Property, it for twins, needs to carry out remarks in systems, and in data acquisition, acquires the information of the difference of the two, when
When identifying that passenger is a member in twins, need to match the different characteristic of default storage again, in order to be identified to it,
Identification is avoided to malfunction.
In one embodiment, referring to Fig. 4, the method for matching the facial image in the preset database includes:
S2100, the facial image of identification is matched with the angled facial image of institute in presetting database；
Since the facial image of multiple angles, such as the side face of positive face and the left and right sides can be acquired during acquiring face
Image, therefore when identifying from image face, it is not limited to only match the profile of positive face, shooting can also be passed through
The side face of human body to carry out identification to passenger.Since the relative position of human body shape of face, face is different, no matter from just
Face or side see there is certain difference, are distinguished by these, can also identify identity of personage to a certain extent.
S2200, facial image of the matching degree more than or equal to preset threshold is chosen as target facial image；
Target facial image is the immediate facial image identified from presetting database.In one embodiment, judge
Method closest to facial image is and to calculate its matching by being compared one by one to the facial image in presetting database
Degree chooses matching degree and is greater than or equal to the facial image of preset threshold as target facial image.The method of the calculating of matching degree
Have very much, in one embodiment, can be by each characteristic point in extracting facial image, and it is a pair of to carry out one to each characteristic point
Than each similar features point increases default score value, to obtain corresponding matching degree.Matching degree most, then means the phase of the two
It is most like characteristic point, it can be understood as the two is similar.
S2300, target facial image mapped identity information and account information are obtained.
Since in the preset database, facial image and identity information and account information are interrelated, therefore pass through step
After S2200 obtains target facial image, the corresponding identity information of target facial image and account information can be obtained.With into
One step judges whether the identity information of the target facial image and account information meet preset condition.
But due to there may be growing the case where comparing picture, for example, the people having relationship by blood or twins etc., nothing
Still there may be certain similarity from side by from front, therefore phase may be will appear from some angle in identification process
Like the same situation of matching degree, therefore, facial image of the matching degree more than or equal to preset threshold is being chosen as mesh described
Before marking facial image, referring to Fig. 5, further include:
S2400, judge whether matching degree is greater than 1 more than or equal to the quantity of the facial image of preset threshold；
S2500, when quantity is greater than 1, obtain the facial image of the passenger another angle and match.
When there is the same facial image of another or multiple matching degrees, due to when acquiring the facial image of passenger
The image of multiple angles is also acquired simultaneously, therefore chooses other angles again from image captured by photographic device or video
Facial image carries out face contour extraction, and other corresponding families of facial image as the matching degree in presetting database
The facial image superintended and directed is compared one by one, and the facial image matching degree for choosing other angles is highest as target facial image.
Whether S3000, the detection facial image meet preset condition, allow when meeting preset condition current and from institute
It states in facial image mapped account information and pays transportation expenses.
In one embodiment, the preset condition includes that the identity information of the facial image mapping is believed for legal identity
Breath.Legal identity information includes that the passenger allows to take public transport.For example, in some cases, settable taboo
Only passenger list is included in the criminal for forbidding the personage in list by bus to can be government department's wanted circular, has bad economic letter
Reputation, or there is that puts on record to have theft or the people of other improper behaviors in public transport, by shooting image frame and carry out
Identification of Images obtains portrait mapped record information, as the artificial above-mentioned personnel that no through traffic, can send out relevant information
It send into security officer's terminal, in order to be handled in time.
In another embodiment, the preset condition includes that the remaining sum in the account information of the facial image mapping is greater than
Or it is equal to threshold value or the remaining sum of at least one and the interlock account of the account information is greater than or equal to threshold value.
Different public transport has different prices, for example taking subway starting price is 2 yuan, and take bus starting fare
Lattice are 1 yuan, and taking price of taxi starting is 10 yuan, different threshold values can be arranged according to specific application.Know when passing through
Others' face image detect in the account information of the passenger when prestoring the amount of money lower than the threshold value, prompted, and forbid going together,
In order to carry out booking and supplement processing with money.
In one embodiment, also settable interlock account, and oneself account information and other people account can be carried out into
Row binding, when Sorry, your ticket has not enough value in the account of oneself, deducts phase from the account information being associated by way of authorization
The expense answered.Such as family of three, everyone has an account by father, mother and child, when child to account information
In when Sorry, your ticket has not enough value, correlative charges can be deducted from the account of the father or mother that are associated, in order to which child can normally make
Use the vehicles.
Further, in another embodiment, associated face can be mapped an account by settable joint account
Family, such as one four mouthfuls, can share one family account, and no matter who takes public transport in the family, all can be at this
Corresponding expense is deducted in a family account, using such mode, one four mouthfuls need to only be supplemented this family account with money
, easy to use.
Further, it manages for convenience, passenger can be added in the identity information and communicates account, in order to work as account
The case where middle remaining sum changes, or when Sorry, your ticket has not enough value timely reminding passengers, and Sorry, your ticket has not enough value when avoiding taking public transport.Into
One step, account can also be communicated to the passenger and sends related public transport information, in order to which passenger understands traffic condition.
Communicate account can with when phone number, wechat account, QQ account or mailbox etc..For example passenger understands remaining sum variation for convenience
Situation, can be reminded by short message or wechat remind etc. modes, by the money currently deducted and who how much amount of money used
Change conditions inform account contact person, and in order to understand account dynamic in time, further, the content of notice may also include trip
Time, trip the information such as place, conveniently trace Mobile state, be especially suitable for the trip of parental control child.
Further, by binding face and account, the available passenger rides number, riding time and load zones
Between, facilitate the trip information of acquisition user, and the relevant information that may be used according to the trip information recommended user of user, such as
User is collected into passenger C and takes the working of subway Line 1 daily, when subway 1 is automatically to send out fault message as breaking down
It send into the mobile phone of passenger C to remind.Or the position of public transport is often taken by obtaining passenger, which is provided
The correlation favor information such as market, shop in range provides convenience to people's lives by way of big data.
Further, can also be when first time acquiring passenger's head image information in order to avoid error, while carrying out fingerprint and adopting
Collection takes public transport in order to enter the station in the case where recognition of face failure using fingerprint auxiliary.
The beneficial effect of the application includes:
1) it can be used and once read multiple portraits, by way of more people pass through gate and pay simultaneously, save by bus
Time keeps passenger more convenient by bus；
2) additionally use the mode that interlock account mutually uses in the application simultaneously, facilitate user oneself account balance not
It is current in time in the case where foot；
3) it also discloses through interlock account, prompting of being deducted fees and gone on a journey, facilitate user to remaining sum and goes out in the application
Traveling journey is into line trace and retrospect；
4) by recognition of face, the personnel for taking public transport can be monitored, need to order to arrest when discovery government department or
Forbid the personnel for taking public transport that can find in time, takes measures on customs clearance in time；
5) by obtaining passenger's trip data, big data analysis is carried out, according to the vehicles and correlation of passenger's trip
Location information provides related service information, achievees the purpose that wisdom is gone on a journey.
On the other hand, the application discloses a kind of transit trip control device, referring to Fig. 6, including:
It obtains module 1000: being configured as executing acquisition into one or more passengers' in public transport compass of competency
Facial image, the facial image include facial contour feature；
Processing module 2000: it is configured as execution and matches the facial image, the preset data in the preset database
It include facial image collected and the set with the identity information of the facial image phase mapping and account information in library；
Execution module 3000: being configured as executing and detect whether the facial image meets preset condition, default when meeting
Allow current when condition and pays transportation expenses from the facial image mapped account information.
Further, further includes:
Input module: it is configured as executing the video image in captured public transport compass of competency is input to nerve
In network model；
Identification module: it is configured as executing the one or more portraits identified in the video image；
Extraction module: it is configured as executing to each portrait progress In vivo detection to extract corresponding facial contour feature.
Further, each passenger's acquisition has the facial image storage of multiple angles in the database, further includes:
First matching module: it is configured as executing the angled people of institute in the facial image and presetting database by identification
Face image is matched；
Object selection module: it is configured as executing and chooses facial image of the matching degree more than or equal to preset threshold as mesh
Mark facial image；
Identity obtains module: being configured as executing acquisition target facial image mapped identity information and account information.
Further, further includes:
Judgment module: be configured as execute judge matching degree more than or equal to preset threshold facial image quantity whether
Greater than 1；
Second matching module: it is configured as executing when quantity is greater than 1, obtains the facial image of another angle of the passenger
And it is matched.
Further, it is legal identity information that the preset condition, which includes the identity information of the facial image mapping,.
Further, the preset condition includes that the remaining sum in the account information of the facial image mapping is greater than or equal to
Threshold value or the remaining sum of at least one and the interlock account of the account information are greater than or equal to threshold value.
Further, the identity information further includes that passenger communicates account, further includes:
Information sending module: it is configured as executing to communications account transmission public transport information or account information variation
Notice.
It is one-to-one since transit trip control device disclosed above is transit trip control method
Product structure, its working principle is that the same, details are not described herein again.
The embodiment of the present invention provides computer equipment basic structure block diagram and please refers to Fig. 6.
The computer equipment includes processor, non-volatile memory medium, memory and the net connected by system bus
Network interface.Wherein, the non-volatile memory medium of the computer equipment is stored with operating system, database and computer-readable finger
It enables, control information sequence can be stored in database, when which is executed by processor, may make that processor is real
A kind of existing transit trip control method.The processor of the computer equipment supports whole for providing calculating and control ability
The operation of a computer equipment.Computer-readable instruction can be stored in the memory of the computer equipment, this is computer-readable
When instruction is executed by processor, processor may make to execute a kind of transit trip control method.The net of the computer equipment
Network interface is used for and terminal connection communication.It will be understood by those skilled in the art that structure shown in Fig. 6, only with this Shen
Please the relevant part-structure of scheme block diagram, do not constitute the limit for the computer equipment being applied thereon to application scheme
Fixed, specific computer equipment may include perhaps combining certain components or tool than more or fewer components as shown in the figure
There is different component layouts.
The status information for prompting behavior that computer equipment is sent by receiving associated client, i.e., whether associated terminal
It opens prompt and whether user closes the prompt task.By verifying whether above-mentioned task condition is reached, and then eventually to association
End sends corresponding preset instructions, so that associated terminal can execute corresponding operation according to the preset instructions, to realize
Effective supervision to associated terminal.Meanwhile when prompt information state and preset status command be not identical, server end control
Associated terminal persistently carries out jingle bell, the problem of to prevent the prompt task of associated terminal from terminating automatically after executing a period of time.
The present invention also provides a kind of storage mediums for being stored with computer-readable instruction, and the computer-readable instruction is by one
When a or multiple processors execute, so that one or more processors execute transit trip control described in any of the above-described embodiment
Method processed.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, which can be stored in a computer-readable storage and be situated between
In matter, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, storage medium above-mentioned can be
The non-volatile memory mediums such as magnetic disk, CD, read-only memory (Read-Only Memory, ROM) or random storage note
Recall body (Random Access Memory, RAM) etc..
It should be understood that although each step in the flow chart of attached drawing is successively shown according to the instruction of arrow,
These steps are not that the inevitable sequence according to arrow instruction successively executes.Unless expressly stating otherwise herein, these steps
Execution there is no stringent sequences to limit, can execute in the other order.Moreover, at least one in the flow chart of attached drawing
Part steps may include that perhaps these sub-steps of multiple stages or stage are not necessarily in synchronization to multiple sub-steps
Completion is executed, but can be executed at different times, execution sequence, which is also not necessarily, successively to be carried out, but can be with other
At least part of the sub-step or stage of step or other steps executes in turn or alternately.
The above is only some embodiments of the invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (10)
1. a kind of transit trip control method characterized by comprising
The facial image of the one or more passengers entered in public transport compass of competency is obtained, the facial image includes face
Contour feature；
Match the facial image in the preset database, include in the presetting database facial image collected and with
The identity information of the facial image phase mapping and the set of account information；
It detects whether the facial image meets preset condition, allows when meeting preset condition current and from the facial image
Transportation expenses are paid in mapped account information.
2. transit trip control method according to claim 1, which is characterized in that described obtain enters public transport
The method of the facial image of one or more passengers in compass of competency includes:
Video image in captured public transport compass of competency is input in neural network model；
Identify one or more portraits in the video image；
In vivo detection is carried out to extract corresponding facial contour feature to each portrait.
3. transit trip control method according to claim 1, which is characterized in that each passenger's acquisition has multiple angles
In the database, the method for matching the facial image in the preset database includes: for the facial image storage of degree
The facial image of identification is matched with the angled facial image of institute in presetting database；
It chooses matching degree and is greater than or equal to the facial image of preset threshold as target facial image；
Obtain target facial image mapped identity information and account information.
4. transit trip control method according to claim 3, which is characterized in that described to be greater than in selection matching degree
Or equal to preset threshold facial image as target facial image before, further includes:
Judge whether matching degree is greater than 1 more than or equal to the quantity of the facial image of preset threshold；
When quantity is greater than 1, obtains the facial image of the passenger another angle and match.
5. transit trip control method according to claim 1, which is characterized in that the preset condition includes described
The identity information of facial image mapping is legal identity information.
6. transit trip control method according to claim 1, which is characterized in that the preset condition includes described
Remaining sum in the account information of facial image mapping is greater than or equal to threshold value or at least one being associated with the account information
The remaining sum of account is greater than or equal to threshold value.
7. transit trip control method according to claim 1, which is characterized in that the identity information further includes multiplying
Visitor's communication account, further includes:
Public transport information is sent to the communications account or account information changes notice.
8. a kind of transit trip control device characterized by comprising
It obtains module: being configured as executing the face figure for obtaining the one or more passengers entered in public transport compass of competency
Picture, the facial image include facial contour feature；
Processing module: it is configured as execution and matches the facial image in the preset database, include in the presetting database
Facial image collected and set with the identity information of the facial image phase mapping and account information；
Execution module: it is configured as executing and detects whether the facial image meets preset condition, permit when meeting preset condition
Perhaps it passes through and pays transportation expenses from the facial image mapped account information.
9. a kind of computer equipment, including memory and processor, it is stored with computer-readable instruction in the memory, it is described
When computer-readable instruction is executed by the processor, so that the processor executes such as any one of claims 1 to 7 right
It is required that the step of described transit trip control method.
10. a kind of storage medium for being stored with computer-readable instruction, the computer-readable instruction is handled by one or more
When device executes, so that one or more processors execute the public transport as described in any one of claims 1 to 7 claim
The step of control method of going on a journey.
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| CN201811349085.9A CN109636397A (en) | 2018-11-13 | 2018-11-13 | Transit trip control method, device, computer equipment and storage medium |
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|---|---|---|---|
| CN201811349085.9A CN109636397A (en) | 2018-11-13 | 2018-11-13 | Transit trip control method, device, computer equipment and storage medium |
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| CN201811349085.9A Pending CN109636397A (en) | 2018-11-13 | 2018-11-13 | Transit trip control method, device, computer equipment and storage medium |
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Application publication date: 20190416 |