CN114663773B - Multi-node cooperative vehicle identification method, device and system and storage medium - Google Patents
Multi-node cooperative vehicle identification method, device and system and storage medium Download PDFInfo
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- CN114663773B CN114663773B CN202210540979.6A CN202210540979A CN114663773B CN 114663773 B CN114663773 B CN 114663773B CN 202210540979 A CN202210540979 A CN 202210540979A CN 114663773 B CN114663773 B CN 114663773B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
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- G—PHYSICS
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- G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
- G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
- G07B15/02—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems
Abstract
A multi-node cooperative vehicle identification method, a device, a system and a storage medium thereof are provided, wherein the multi-node cooperative vehicle identification method comprises the following steps: when a unlicensed vehicle enters the field, acquiring an image of the vehicle to generate first characteristic information, acquiring wireless fidelity media access control information of the vehicle and the periphery to generate a first wireless fidelity media access control information set, and generating and storing an entrance record of the vehicle; when an unlicensed vehicle leaves, generating second characteristic information and a second wireless fidelity media access control information set, determining an entrance record of the vehicle leaving according to the second characteristic information and the second wireless fidelity media access control information set, and charging the vehicle leaving according to the entrance time of the entrance record. According to the scheme provided by the embodiment, the vehicle can be identified through the characteristic information and the WiFi MAC, the passing efficiency is high, and the user experience is good.
Description
Technical Field
The present disclosure relates to parking charging technologies, and in particular, to a method, an apparatus, a system, and a storage medium for multi-node cooperative vehicle identification.
Background
In order to improve the vehicle passing efficiency, the license plate automatic identification system is usually installed at the entrance and exit of the parking lot of the current large business super, residence and park. According to the license plate information and the parking duration, the system can generate corresponding parking cost. However, in reality, the license plate is always damaged or not hung, and the driver and the passenger generally need to get tickets/register and enter the vehicle in a mode of scanning the two-dimensional code by the mobile phone because the license plate information cannot be acquired. Because the link of self-service operation of personnel is added, the process is complex and uncontrollable, and the passing efficiency and the user experience are influenced.
Another solution is to associate the facial image of the driver with the vehicle type information and start calculating the parking time and the fee by collecting the facial image and the vehicle type information of the driver of the vehicle. The scheme relates to the collection of biological information and has legal risks; in addition, in order to ensure the automatic acquisition effect of the human face in the automobile, a flashing light needs to be configured in the system, which causes light pollution to drivers and passengers; and if the system needs to actively cooperate the passengers to enter and exit (such as opening a window probe or getting off the vehicle), the blind passing experience of the entrance and the exit is influenced.
Disclosure of Invention
The embodiment of the application provides a multi-node cooperative vehicle identification method, a multi-node cooperative vehicle identification device, a multi-node cooperative vehicle identification system and a storage medium, and the passing efficiency of unlicensed vehicles can be improved.
The embodiment of the application provides a multi-node cooperative vehicle identification method, which comprises the following steps:
when a unlicensed vehicle enters, acquiring an image of the vehicle to generate first characteristic information, acquiring wireless fidelity media access control information of the vehicle and the periphery to generate a first wireless fidelity media access control information set, generating and storing an entry record of the vehicle, wherein the entry record comprises identification information distributed to the vehicle, the first characteristic information, the first wireless fidelity media access control information set and the entry time of the vehicle;
when an unlicensed vehicle leaves, acquiring an image of the vehicle leaving the vehicle to generate second characteristic information, acquiring wireless fidelity media access control information of the vehicle leaving the vehicle and the periphery to generate a second wireless fidelity media access control information set, determining an entrance record of the vehicle leaving the vehicle according to the second characteristic information and the second wireless fidelity media access control information set, and charging the vehicle leaving the vehicle according to the entrance time of the entrance record.
In an exemplary embodiment, the obtaining the image of the vehicle at the departure generates second feature information, and the obtaining the wifi media access control information of the vehicle and the surroundings at the departure generates a second wifi media access control information set includes:
acquiring an image of the vehicle which is on the scene to generate second characteristic information, and acquiring wireless fidelity media access control information of the vehicle which is on the scene and the periphery to generate a second wireless fidelity media access control information set when the second characteristic information is matched with a plurality of entrance records;
the method further comprises the following steps: and when the second characteristic information is only matched with one entry record, charging the vehicles for leaving according to the entry time of the matched entry record.
In an exemplary embodiment, determining the entry record of the departing vehicle according to the second characteristic information and the second set of wireless fidelity medium access control information comprises: and when the second wireless fidelity medium access control information set only has intersection with the first wireless fidelity medium access control information set of one of the matched entry records, the entry record with the intersection is the entry record of the vehicle which is out of the field.
In an exemplary embodiment, the method further comprises:
when the unlicensed vehicle is in the field, generating third characteristic information according to the image of the unlicensed vehicle acquired by a camera passed by the unlicensed vehicle, generating a third wireless fidelity media access control information set according to the vehicle and the wireless fidelity media access control information around the vehicle, generating and storing an in-field record of the vehicle, wherein the in-field record comprises the identification information of the camera, the third characteristic information and the third wireless fidelity media access control information set, and the camera acquires the acquisition time of the image of the unlicensed vehicle.
In an exemplary embodiment, the method further comprises:
when the second wireless fidelity media access control information set is intersected with the first wireless fidelity media access control information set of more than one entry record in the matched entry records, the following backtracking steps are executed: calling a history video, determining that other vehicles similar to the vehicle leaving the field do not exist in the history video within the time when the vehicle leaving the field arrives at the current camera from the last camera, and acquiring a field record of the vehicle leaving the field in the period when the vehicle passes through the last camera, wherein the field record is called a target field record, and the two vehicles are similar, namely the characteristic information of the two vehicles meets a preset matching condition;
and when the target in-field record only has intersection with one of the matched plurality of entrance records, charging the vehicles which come out according to the entrance time of the entrance records with the intersection.
In an exemplary embodiment, the method further comprises:
when the intersection exists between the target in-field record and more than one of the matched entry records, taking the previous camera as the current camera, and re-executing the backtracking step until a camera, called a target camera, is found, wherein the intersection exists between the target in-field record and only one of the matched entry records, or all cameras, passing by the vehicle, in the field, are found;
when the target camera is found, charging the vehicles which are out of the field according to the entrance time of the entrance records with the intersection;
and when the target camera is not found, prompting to carry out manual charging.
In an exemplary embodiment, the first feature information and the second feature information are semi-structured feature vectors generated by a preset neural network model.
The disclosed embodiment provides a multi-node cooperative vehicle identification device, which comprises a memory and a processor, wherein the memory stores a program, and the program realizes the multi-node cooperative vehicle identification method of any one of the above embodiments when being read and executed by the processor.
The disclosed embodiments provide a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement a multi-node cooperative vehicle identification method according to any of the above embodiments.
The disclosed embodiment provides a multi-node cooperative vehicle identification system, comprising a camera located at an entrance, a camera located at an exit and a background server, wherein,
the camera at the entrance is configured to acquire an image of the vehicle when an unlicensed vehicle enters the entrance, or acquire the image of the vehicle to generate first characteristic information, and send the image or the first characteristic information and the entrance time of the vehicle to the background server; acquiring wireless fidelity media access control information of the vehicle and the periphery to generate a first wireless fidelity media access control information set and send the first wireless fidelity media access control information set to the background server;
the camera at the exit is configured to acquire an image of a vehicle on the scene when the unlicensed vehicle is on the scene, or acquire second characteristic information generated by the vehicle on the scene, send the image or the second characteristic information to the background server, and acquire wireless fidelity media access control information of the vehicle on the scene and the periphery, generate a second wireless fidelity media access control information set and send the second wireless fidelity media access control information set to the background server;
the background server is configured to receive an image sent by a camera at an entrance to generate first characteristic information, or receive the first characteristic information sent by the camera at the entrance, receive a first wireless fidelity medium access control information set sent by the camera at the entrance, generate and store an entry record of a vehicle, wherein the entry record comprises identification information allocated to the vehicle, the first characteristic information, the first wireless fidelity medium access control information set and entry time of the vehicle; and receiving an image sent by a camera at an exit to generate second characteristic information, or receiving the second characteristic information sent by the camera at the exit, receiving a second wireless fidelity medium access control information set sent by the camera at the exit, determining an entry record of a vehicle which is out of the field according to the second characteristic information and the second wireless fidelity medium access control information set, and charging the vehicle which is out of the field according to the entry time of the entry record.
Compared with the related art, the method, the device, the system and the storage medium for multi-node cooperative vehicle identification are provided, and the multi-node cooperative vehicle identification method comprises the following steps: when a unlicensed vehicle enters, acquiring an image of the vehicle to generate first characteristic information, acquiring wireless fidelity media access control information of the vehicle and the periphery to generate a first wireless fidelity media access control information set, generating and storing an entry record of the vehicle, wherein the entry record comprises identification information distributed to the vehicle, the first characteristic information, the first wireless fidelity media access control information set and the entry time of the vehicle; when an unlicensed vehicle leaves, acquiring an image of the vehicle which leaves a field to generate second characteristic information, acquiring wireless fidelity media access control information of the vehicle which leaves the field and the periphery to generate a second wireless fidelity media access control information set, determining an entrance record of the vehicle which leaves the field according to the second characteristic information and the second wireless fidelity media access control information set, and charging the vehicle which leaves the field according to the entrance time of the entrance record. The scheme that this embodiment provided can carry out the discernment of vehicle through characteristic information and wiFi MAC, need not artifical the participation (manual registration, sweep the sign indicating number etc.), and the current efficiency is high, and user experience is good, can discern the unlicensed vehicle of the same style, and need not discernment user's biological information, can avoid the law risk.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. Other advantages of the present application may be realized and attained by the instrumentalities and combinations particularly pointed out in the specification and the drawings.
Drawings
The drawings are intended to provide an understanding of the present disclosure, and are to be considered as forming a part of the specification, and are to be used together with the embodiments of the present disclosure to explain the present disclosure without limiting the present disclosure.
FIG. 1 is a flow chart of a multi-node coordinated vehicle identification method provided in an exemplary embodiment;
FIG. 2 is a schematic diagram of a multi-node coordinated vehicle identification system provided in an exemplary embodiment;
FIG. 3 is a schematic diagram illustrating an intelligent IPC distribution in a multi-node coordinated vehicle identification system according to an exemplary embodiment;
FIG. 4 is a block diagram of a multi-node coordinated vehicle identification apparatus according to an exemplary embodiment.
Detailed Description
The present application describes embodiments, but the description is illustrative rather than limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are possible. Any feature or element of any embodiment may be used in combination with or instead of any other feature or element in any other embodiment, unless expressly limited otherwise.
The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive concept as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive aspects to form yet another unique inventive aspect, as defined by the claims. Thus, it should be understood that any of the features shown and/or discussed in this application may be implemented alone or in any suitable combination. Accordingly, the embodiments are not limited except as by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.
Further, in describing representative embodiments, the specification may have presented the method and/or process as a particular sequence of steps. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. Other orders of steps are possible as will be understood by those of ordinary skill in the art. Therefore, the particular order of the steps set forth in the specification should not be construed as limitations on the claims. Further, the claims directed to the method and/or process should not be limited to the performance of their steps in the order written, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the embodiments of the present application.
The embodiment of the disclosure provides a multi-node cooperative vehicle identification method, vehicles are cooperatively identified based on vehicle identification and WiFi wireless sniffing, the passing efficiency same as that of a vehicle with a license can be realized, and the legal risk possibly faced by a face acquisition scheme is avoided.
Fig. 1 is a flowchart of a multi-node cooperative vehicle identification method according to an embodiment of the present disclosure. As shown in fig. 1, the method for identifying a unlicensed vehicle and parking fee provided by this embodiment includes:
The scheme that this embodiment provided carries out the discernment of vehicle through characteristic information and wiFi MAC, need not artifical participation (manual registration, sweep the sign indicating number etc.), and the traffic is efficient, and user experience is good, can discern the unlicensed vehicle of the same style, and need not discernment user's bioinformation, can avoid legal risk.
In the embodiment, the field is a parking lot, and cameras are arranged at the entrance and the exit of the parking lot for image acquisition; one or more cameras may be located within the parking lot.
In an exemplary embodiment, the unlicensed vehicle may be detected by license plate location and identification. When the license plate can not be identified, the vehicle is a unlicensed vehicle.
In an exemplary embodiment, the method further comprises, when a vehicle with a license plate enters the field, identifying the license plate of the vehicle, and recording the license plate and the time of entry of the vehicle; when a vehicle with a license plate leaves, the license plate of the vehicle is identified, and charging is carried out according to the entrance time corresponding to the license plate. The scheme provided by the embodiment can charge the vehicles with license plates directly according to the license plates, and is simple and convenient to implement and high in efficiency. But the embodiment of the present disclosure is not limited thereto, and a licensed vehicle may be identified according to the characteristic information and the WIFI MAC information.
In an exemplary embodiment, acquiring an image of the vehicle on the scene generates second feature information, and acquiring WiFi MACs of the vehicle on the scene and surroundings generates a second WiFi MAC information set, including:
acquiring an image of the vehicle which is on the scene to generate second characteristic information, and acquiring the vehicle which is on the scene and WiFi MAC information around the vehicle to generate a second WiFi MAC information set when the second characteristic information is matched with a plurality of entrance records;
the method further comprises the following steps: and when the second characteristic information is only matched with one entry record, charging the vehicles for leaving according to the entry time of the matched entry record.
The entry record matched with the second characteristic information is as follows: and the first characteristic information and the second characteristic information to be matched are similar to each other, wherein the similarity of the characteristic information can be that the two pieces of characteristic information meet a preset matching condition. Taking the feature information as an example of the feature vector, when comparing the feature vectors, if the euclidean distance or the cosine distance between the two is less than or equal to a preset threshold, the two feature vectors are similar. The similarity of the two pieces of feature information includes a case where the two pieces of feature information are the same.
In this embodiment, when only one entry record is matched according to the second feature information, the identification and the charging can be performed without acquiring WiFi MAC information, so that the charging can be simplified.
In an exemplary embodiment, the first feature information and the second feature information may be semi-structured feature vectors generated by a preset neural network model. The preset neural network model can be a neural network model obtained through training, and the semi-structured feature vector can be obtained by inputting the obtained image into the preset neural network model. However, the embodiment of the present disclosure is not limited thereto, and the first feature information and the second feature information may be vehicle type information obtained based on neural network model recognition. The semi-structured feature vector is used, and in the face of new vehicle styles, manufacturers do not need to introduce new vehicle data to monitor and learn the neural network model any more, the trouble of periodically upgrading parking lot equipment is avoided, and compared with the semi-structured feature vector obtained through images, the semi-structured feature vector has the advantages of lower calculation amount of vehicle type information, high running speed, low requirement on system hardware and low cost.
In an exemplary embodiment, the determining the entry record of the departing vehicle according to the second characteristic information and the second WiFi MAC information set includes: and when the second WiFi MAC information set only has intersection with the first WiFi MAC information set of one of the matched entry records, the entry record with the intersection is the entry record of the vehicle which comes out. Generally, the number of the unlicensed vehicles in the parking lot is small, the probability that the unlicensed vehicles with the same vehicle type enter the same parking lot is lower, and therefore only one entrance record can be matched, and therefore the vehicles can be conveniently identified.
In an exemplary embodiment, the method further comprises:
when the unlicensed vehicle is in the field, generating third characteristic information according to the image of the unlicensed vehicle acquired by a camera passed by the unlicensed vehicle, generating a third WiFi MAC information set by the vehicle and WiFi MAC information around the vehicle, generating and storing an in-field record of the vehicle, wherein the in-field record comprises identification information of the camera, the third characteristic information and the third WiFi MAC information set, and the camera acquires the acquisition time of the image of the unlicensed vehicle; in this embodiment, when the vehicle is in the field, record the relevant characteristic information of vehicle and wiFi MAC information set, carry out the backtracking of vehicle when being convenient for match many records of entering into when going out.
In an exemplary embodiment, the method further comprises:
when the second WiFi MAC information set intersects with the first WiFi MAC information set of more than one entry record in the multiple matched entry records, performing the following backtracking step: calling a history video, determining that other vehicles similar to the vehicle leaving the field do not exist in the history video within the time when the vehicle leaving the field arrives at the current camera from the last camera, and acquiring the field record of the last camera within the time period when the vehicle leaving the field passes through the last camera, wherein the field record is called target field record; the similarity of the two vehicles means that the characteristic information of the two vehicles meets a preset matching condition; that is, the characteristic information of the two vehicles is similar;
and when the target in-field record only has intersection with one of the matched plurality of entrance records, charging the vehicles which come out according to the entrance time of the entrance records with the intersection.
In an exemplary embodiment, the method further comprises:
when the intersection exists between the target in-field record and more than one of the matched multiple entry records, taking the previous camera as the current camera, and re-executing the backtracking step until a camera, called a target camera, is found out, wherein the intersection exists between the target in-field record and only one of the matched multiple entry records, or all cameras, through which the vehicle leaving the field passes, in the field are found out;
when the target camera is found, charging the vehicles which come out according to the entrance time of the entrance records with the intersection;
and when the target camera is not found, prompting to carry out manual charging.
According to the scheme provided by the embodiment of the disclosure, when vehicles of the same type may exist near the vehicles on the spot, the vehicles on the spot can be determined in a backtracking manner due to the fact that the probability that the same vehicles reach the exit through the same route is low, and the identification and the charging of the vehicles are realized.
In an exemplary embodiment, the prompting may be performed using one or a combination of the following: voice prompt and display screen prompt.
In an exemplary embodiment, when there is an intersection between the second WiFi MAC information set and the first WiFi MAC information set of more than one entry record in the matched entry records, prompting manual charging; or after the backtracking step is executed once, when the intersection exists between the target field record and the plurality of entrance records, prompting manual charging.
The technical solution of the embodiments of the present disclosure is further explained by an example.
In the embodiment of the disclosure, when a vehicle enters a field, a camera collects an image of the vehicle, generates a semi-structured feature vector under a corresponding neural network model for the vehicle according to the collected image, collects WiFi MAC information sets around the moment through a WiFi Sniffer (WiFi Sniffer) module carried by the camera, and sends the feature vector, the WiFi MAC information sets and the entry time of the vehicle to a background server, and the background server stores the feature vector, the WiFi MAC information sets and the entry time as entry records of the vehicle in a database; if two similar unlicensed vehicles (vehicles with similar characteristic information) enter, the characteristic vectors and the WiFi MAC information sets of different vehicles are stored separately.
When the vehicle leaves, if the unlicensed vehicle is detected, the cooperation background server judges whether other vehicles similar to the vehicle exist, and if the unlicensed vehicle does not exist (namely, only one admission record is matched), the vehicles are directly matched for charging. If the WiFi MAC information set exists (namely a plurality of entrance records are matched), the WiFi MAC information set at the moment is collected, if the WiFi MAC information set only has intersection with the WiFi MAC information set of one of the matched entrance records, the vehicle can be identified, and charging is carried out according to the entrance time of the vehicle.
If the collected WiFi MAC information set is intersected with the WiFi MAC information sets in the matched entry records, which vehicle in similar vehicles cannot be determined, whether other vehicles similar to the vehicles on the scene appear in the period from the lower part of the last camera to the camera is judged through backtracking historical video, if not, the feature vector on the scene is sent to the last camera, and the last camera is requested to feed back the WiFi MAC information set collected when the vehicle passes through the last camera; if the WiFi MAC information set fed back by the last camera only intersects with one entrance record, charging can be carried out according to the entrance time in the entrance record with the intersection. And if the WiFi MAC information set fed back by the previous camera still intersects with the entrance records, executing the same operation until the WiFi MAC information set fed back by a certain camera only intersects with one entrance record, and charging according to the entrance time in the entrance records with the intersection.
FIG. 2 is a schematic diagram of a multi-node coordinated vehicle identification system provided in an exemplary implementation. As shown in fig. 2, the multi-node cooperative vehicle identification system includes: the intelligent IPC monitoring system comprises an intelligent camera (or intelligent IPC), a display screen and a background server, wherein the background server is connected with the intelligent IPC (can be connected in a wired or wireless mode), the display screen is connected with the intelligent IPC (can be connected in a wired or wireless mode), or the display screen and the intelligent IPC can be integrated together, wherein:
the intelligent IPC can identify the license plate number and generate a semi-structured feature vector under a neural network model for the unlicensed vehicle. The intelligent IPC can be integrated with a WiFi MAC collector (namely a WiFi Sniffer module) and can collect wireless equipment information near the intelligent IPC, such as the MAC address of a mobile phone of a driver and a passenger of an automobile. The exit and entrance of parking area and inside every crossing can all install intelligent IPC.
The display screen may be placed at the entrance and exit of the parking lot. The display screen at the entrance can prompt the unlicensed vehicle to start WiFi (wireless fidelity) so as to authorize the WiFi Sniffer module to wirelessly collect WiFiMAC (wireless fidelity access control) of the mobile phone of the driver and the passenger, and can display the identified license plate number of the licensed vehicle; the display screen at the exit may prompt the parking time and the amount of the charge for the vehicle. In another exemplary embodiment, a display screen may not be provided, and voice prompt may be used.
The background server is configured to receive, store, retrieve and match the feature vectors uploaded by the intelligent IPC, and support analysis and filtering of WiFi MAC addresses provided by the WiFi Sniffer module of the intelligent IPC to identify the vehicle.
In another exemplary embodiment, the feature vector generation of the vehicle may be performed by the background server, and the intelligent IPC only needs to provide an image or video code stream of the vehicle, which is not limited in this respect.
The multi-node cooperative vehicle identification method provided by the embodiment comprises the following steps:
step 301, after a vehicle enters a field, the intelligent IPC acquires image generation characteristic information and an MAC set;
when a vehicle enters a field, an intelligent camera at an entrance generates a semi-structured feature vector, namely a first feature vector, under a corresponding neural network model for the vehicle, collects WiFi MAC information around the intelligent camera at the moment through WiFi Sniffer carried by the intelligent camera to generate a first WiFi MAC information set, and sends the first feature vector and the first WiFi MAC information set of the vehicle to a database of a background server for storage; and if two similar unlicensed vehicles enter, separately storing the vehicle feature vector, the WiFi MAC information set and the binding relationship.
The intelligent IPC at the entrance acquires the feature vector and the WiFiMAC information set of the vehicle. After an interested target (such as a vehicle/a person) in a video image is subjected to target classification and target positioning, corresponding semi-structured feature vectors are extracted through a deep neural network. The feature vector can be a real number vector of 1 × 128 or 1 × 256, and different types of vehicle targets are mapped by the deep neural network to obtain different feature vectors. When the video image is collected, the intelligent IPC can also acquire surrounding WiFi MAC information through the WiFi Sniffer module. And the intelligent IPC reports the characteristic information, the Wifi MAC information set and the entrance time to the background server.
Supposing that a unlicensed vehicle A0 enters a park area, the background server generates a record of an intelligent IPC snapshot vehicle according to information reported by the intelligent IPC at an entrance, and stores a snapshot time (namely, an entrance time), a characteristic vector and a Wifi MAC information set of the vehicle, wherein the record is called an entrance record. As shown in table 1 below, the entry record may include: the vehicle identification information (namely the vehicle target ID) distributed to the vehicle by the background server, the IPC number (namely the IPC number reporting the characteristic information and the Wifi MAC information set), the characteristic vector, the MAC information (namely the WiFi MAC information set), and the time of entry.
TABLE 1 admission entry List
| Vehicle object ID | IPC numbering | Feature vector | MAC information | Time of admission |
| RecordID1 | 1 | Feature vector A | a1，a2，c，d | ET1 |
In table 1, the actual MAC addresses of the mobile phones of the drivers and passengers in the unlicensed vehicle A0 are a1 and a2. And other MAC addresses c and d belong to mobile phones of other nearby people acquired by intelligent IPC at the entrance and are interference addresses.
Other intelligent IPCs in the field can acquire images of vehicles to generate characteristic vectors and WiFi MAC in vehicle approaches, the characteristic vectors, the WiFi MAC in vehicle approaches and the acquisition time of the images of the acquired vehicles are reported to the background server, and the background server generates records in the field. As shown in table 2, the intrafield records may include: the IPC number (namely the IPC number reporting the characteristic information and the Wifi MAC information set), the characteristic vector, the MAC information (namely the WiFi MAC information set) and the collection time. In an exemplary embodiment, the in-field record may include vehicle identification information (i.e., a vehicle target ID), where the vehicle identification information may be determined according to vehicle identification information in an entry record matched by the feature vector and the WiFi MAC information set, that is, after there is an entry record that is found to be similar to the reported feature vector and has an intersection with the reported WiFi MAC information set, the vehicle identification information of the entry record is used as the identification information of the in-field record; if multiple entry records are found, the field is blank. Taking table 2 as an example, if the feature vector in table 2 is the same as the feature vector in table 1, and there is an intersection between the MAC information in table 2 and the MAC information in table 1 (both include MAC addresses a1, a 2), the vehicle target ID in table 1 is taken as the vehicle target ID recorded in the field in table 2.
TABLE 2 field recording table
| Vehicle object ID | IPC numbering | Feature vector | MAC information | Time of acquisition |
| RecordID1 | 5 | Feature vector A | a1，a2，e，f | ET5 |
Due to the matching of the vehicle feature vectors, the attribute retrieval mode of not searching the license plate of the vehicle has fast response. In another exemplary embodiment, when a vehicle enters a field, the intelligent IPC at the entrance locates and identifies the license plate, if the vehicle has the license plate, the intelligent IPC determines the parking time and the parking cost through the license plate locating and identifying of the vehicle; and if the vehicle is not the licensed vehicle, generating a semi-structured feature vector under a preset neural network model for the vehicle target. Considering that the number of the unlicensed vehicles is small, the number of the feature vectors is not large, and the real-time performance of matching retrieval can be guaranteed.
And step 302, when the unlicensed vehicle leaves, if the characteristic information of the unlicensed vehicle is only matched with one admission record, carrying out charging processing according to the admission time in the matched admission record.
When the vehicle leaves, if the unlicensed vehicle is detected, the cooperation background server judges whether other vehicles similar to the vehicle feature vector exist or not, and if not, the vehicles are directly matched for fee deduction processing.
When the unlicensed vehicle leaves the field, the intelligent IPC at the exit collects video images, and compares the collected characteristic vectors of the vehicle with the characteristic vectors of the unlicensed vehicles which are not left in the background server. If only one entry record is matched through the comparison of the feature vectors, the parking fee is directly calculated according to the time difference between the departure time and the entry time and displayed on a display screen to ask a driver to pay the fee.
Step 303, when the unlicensed vehicle leaves the field, if the feature information of the unlicensed vehicle is matched with a plurality of entrance records, acquiring the unlicensed vehicle at the current moment and a peripheral WiFi MAC information set (namely, a WiFi MAC information set around the intelligent IPC at the place of the field), and when the WiFi MAC information set only intersects with one of the matched entrance records, charging the current time of the field according to the entrance time in the entrance records with the intersection.
When two similar vehicles enter the field, the intelligent IPC of the entrance generates an entrance record for each of the two vehicles, as shown in tables 3 and 4, respectively, and when the feature vectors of the two vehicles are the same or similar, the vehicles are considered to be similar. In this embodiment, the feature vectors of the two are the same.
TABLE 3 entry record TABLE II
| Vehicle object ID | IPC numbering | Feature vector | MAC information | Time of admission |
| RecordID1 | 1 | Feature vector A | a1，a2，c，d | ET1 |
Table 4 entry record table three
| Vehicle object ID | IPC numbering | Feature vector | MAC information | Time of admission |
| RecordID9 | 1 | Feature vector A | a9，e，f | ET9 |
When the unlicensed vehicle leaves the field, the intelligent IPC is used for acquiring video images and comparing the acquired vehicle characteristic vectors with the unlicensed vehicle characteristic vectors which are stored in the background server and do not leave the field. And matching 2 entry records through feature vector comparison, and collecting WiFi MAC information sets around the moment. And if the WiFi MAC information set only has intersection with the WiFi MAC information set of one of the matched 2 entrance records, carrying out charging processing according to the entrance time in the entrance records with the intersection. For example, if the collected WiFi MAC information set is { a1, g, h }, and only an intersection exists with the entry record shown in table 3, it indicates that the vehicle is a vehicle corresponding to the entry record shown in table 3, and charging is performed according to the entry time and the current departure time in table 3.
And 304, when the unlicensed vehicle leaves, if the characteristic information of the unlicensed vehicle is matched with a plurality of entrance records, acquiring a current unlicensed vehicle and a peripheral WiFi MAC information set (namely a WiFi MAC information set around the intelligent IPC at the place of the unlicensed vehicle), and when the WiFi MAC information set and more than one matched entrance record have an intersection, determining the entrance records through backtracking.
If the collected WiFi MAC information set intersects with multiple entrance records, it cannot be determined which vehicle is among the similar vehicles. And if the vehicle has no other similar vehicles in the period from the intelligent IPC of the previous intersection to the intelligent IPC of the exit in the visual field range of the intelligent IPC of the exit, the characteristic vector acquired by the intelligent IPC of the exit is sent to the intelligent IPC of the previous intersection, and the intelligent IPC of the previous intersection is called to feed back the WiFi MAC information set acquired by the intelligent IPC of the previous intersection when the vehicle passes through the intelligent IPC. And if the WiFi MAC information set acquired by the intelligent IPC of the previous intersection only has intersection with the WiFi MAC information set of one of the matched entry records, charging according to the entry record corresponding to the WiFi MAC information set with the intersection.
FIG. 3 is a schematic diagram of an intelligent IPC distribution provided by an exemplary embodiment. The intelligent IPC collection at the exit discovers that the WiFi MAC information sets at the moment are { a1, a9, h, i }, and the WiFi MAC information sets of RecordID1 and RecordID9 have intersection, so that the current vehicle cannot be judged as the vehicle, and the reason is that another vehicle possibly stops nearby.
At this time, the intelligent IPC of other intersections can perform auxiliary judgment. The intelligent IPC at the exit obtains the time point time-A (or the time period) when the current unlicensed vehicle passes through the intelligent IPC at the previous intersection by calling the historical video and backtracking the historical video from the current moment to the front, judges whether the vehicle is similar to the vehicle in the time period when the vehicle passes through the intelligent IPC from the lower part of the intelligent IPC at the previous intersection to the intelligent IPC or not by playing back the video, and sends the characteristic vector and the time-A of the vehicle to the camera at the previous intersection (1), namely the intelligent IPC with the number of 11 if the vehicle does not pass through the intelligent IPC at the previous intersection.
And the intelligent IPC No. 11 searches a WiFi MAC information set collected near the time-A, if the intelligent IPC No. 11 has intersection with only one entry record in the matched entry records in the WiFi MAC information set collected near the time-A, the vehicle is identified according to the entry records with the intersection, such as RecordID1, the RecordID1 is sent to the intelligent IPC at the exit, and the vehicle corresponding to the RecordID1 is charged.
The intelligent IPC at the exit judges that no other similar vehicles pass through the camera at the previous intersection through the history video, and then sends the query request, so that the judgment error can be avoided. If other vehicles similar to the vehicle on the departure exist, the manual charging can be directly prompted.
If the last intelligent IPC, namely No. 11 intelligent IPC finds that the WiFi MAC information set of time-A still intersects with a plurality of entrance records, the same backtracking operation is executed. The intelligent IPC No. 11 backtracks the previous history video from time-A according to the feature vector of the unlicensed vehicle received by the intelligent IPC at the exit, judges which intelligent IPC the unlicensed vehicle has passed through in history, such as the intelligent IPC12, and finds the time-B when the unlicensed vehicle passes through the intelligent IPC12 through video playback; and no other vehicles similar to the vehicles on the spot pass through the history video from time-B to time-A, please intelligent IPC12 to search the WiFi MAC information set collected near the time-B. If the intelligent IPC12 finds that an intersection exists only with one entry record in a plurality of entry records matched with vehicles on the spot in a WiFi MAC information set collected near the time-B moment, the vehicles are identified according to the entry records with the intersection, for example, recordID1, the RecordID1 is sent to the intelligent IPC at the exit, and the vehicles corresponding to the RecordID1 are charged.
If the intelligent IPC12 finds that the WiFi MAC information set collected by the time-B is intersected with the entrance records of a plurality of corresponding eigenvector vehicles, similar operation is carried out by referring to the intelligent IPC 11.
The possibility of multiple similar unlicensed vehicles passing the same path at the same time is extremely small, and so long as such extremes do not occur, the above-described approach is feasible. If an extreme situation occurs, namely a certain camera finds that a proper previous path of camera cannot be found, the information that the intelligent IPC at the exit cannot assist is fed back, and the intelligent IPC at the exit prompts artificial charging on a display screen.
The scheme provided by the embodiment does not need manual registration/code scanning or face collection, and can solve the problem that multiple unlicensed vehicles with the same type come in and go out to park in real life, so that the unlicensed vehicles can achieve the same passing efficiency as the licensed vehicles.
As shown in fig. 4, an embodiment of the present disclosure provides a multi-node cooperative vehicle identification apparatus 40, which includes a memory 410 and a processor 420, where the memory 410 stores a program, and when the program is read and executed by the processor 420, the program implements the multi-node cooperative vehicle identification method according to any one of the above embodiments.
A computer-readable storage medium storing one or more programs, which are executable by one or more processors, to implement the multi-node cooperative vehicle identification method according to any of the embodiments described above.
The disclosed embodiment provides a multi-node cooperative vehicle identification system, comprising a camera located at an entrance, a camera located at an exit and a background server, wherein,
the camera at the entrance is configured to acquire an image of the vehicle when an unlicensed vehicle enters the entrance, or acquire the image of the vehicle to generate first characteristic information, and send the image or the first characteristic information and the entrance time of the vehicle to the background server; acquiring WiFi MAC information of the vehicle and the periphery to generate a first WiFi MAC information set and sending the first WiFi MAC information set to the background server;
the camera at the exit is configured to acquire an image of a vehicle on the scene when the unlicensed vehicle leaves, or acquire second feature information generated by the vehicle on the scene, send the image or the second feature information to the background server, and acquire a second WiFi MAC information set generated by the vehicle on the scene and the WiFi MAC information at the periphery and send the second WiFi MAC information set to the background server;
the background server is configured to receive an image sent by a camera at an entrance to generate first feature information, or receive the first feature information sent by the camera at the entrance, receive a first WiFi MAC information set sent by the camera at the entrance, generate and store an entry record of a vehicle, wherein the entry record comprises identification information distributed to the vehicle, the first feature information, the first WiFi MAC information set and entry time of the vehicle; and receiving an image sent by a camera at an exit to generate second characteristic information, or receiving the second characteristic information sent by the camera at the exit, receiving a second WiFi MAC information set sent by the camera at the exit, determining an entry record of a vehicle which exits according to the second characteristic information and the second WiFi MAC information set, and charging the vehicle which exits according to the entry time of the entry record.
In an exemplary embodiment, the multi-node coordinated vehicle identification system may further include at least one camera located within the field. For implementation of the cameras located in the field, please refer to the foregoing embodiments, and details are not repeated.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
Claims (8)
1. A multi-node cooperative vehicle identification method is characterized by comprising the following steps:
when a unlicensed vehicle enters, acquiring a first image of the vehicle to generate first characteristic information, acquiring wireless fidelity media access control information of the vehicle and the periphery to generate a first wireless fidelity media access control information set, generating and storing an entry record of the vehicle, wherein the entry record comprises identification information distributed to the vehicle, the first characteristic information, the first wireless fidelity media access control information set and entry time of the vehicle;
when the unlicensed vehicle is in the field, generating third characteristic information according to a third image of the unlicensed vehicle acquired by a camera passed by the unlicensed vehicle, generating a third wireless fidelity media access control information set according to the vehicle and the wireless fidelity media access control information of the periphery, generating and storing an in-field record of the vehicle, wherein the in-field record comprises identification information of the camera, the third characteristic information and the third wireless fidelity media access control information set, and the camera acquires the acquisition time of the third image of the unlicensed vehicle;
when a vehicle without a license is present, acquiring a second image of the vehicle to generate second characteristic information, and when the second characteristic information is matched with a plurality of entrance records, acquiring the wireless fidelity media access control information of the vehicle present and the periphery to generate a second wireless fidelity media access control information set;
when the second wireless fidelity media access control information set intersects with the first wireless fidelity media access control information set of more than one entry record in the matched entry records, the following backtracking steps are executed: calling a history video of a current camera, determining the time when the vehicle is arrived at the current camera from the last camera, and acquiring an in-field record of the last camera in the time period when the vehicle passes through the last camera when other vehicles similar to the vehicle are not present in the history video, wherein the in-field record is called a target in-field record, and the similarity of two vehicles means that the characteristic information of the two vehicles meets a preset matching condition;
and when the intersection exists between the third wireless fidelity media access control information set recorded in the target field and the first wireless fidelity media access control information set of one entry record in the matched entry records, charging the vehicles on the departure according to the entry time of the entry record with the intersection.
2. The multi-node cooperative vehicle identification method according to claim 1,
the method further comprises the following steps: and when the second characteristic information is only matched with one entry record, charging the vehicles for leaving according to the entry time of the matched entry record.
3. The multi-node coordinated vehicle identification method according to claim 2, further comprising: and when the second wireless fidelity media access control information set only has intersection with the first wireless fidelity media access control information set of one of the matched entry records, the entry record with the intersection is the entry record of the vehicle which is out of the field, and the vehicle which is out of the field is charged according to the entry record of the vehicle which is out of the field.
4. The multi-node coordinated vehicle identification method according to claim 1, further comprising:
when the intersection exists between the third wireless fidelity media access control information set recorded in the target field and the first wireless fidelity media access control information set of more than one entry record in the matched entry records, taking the last camera as the current camera, and re-executing the backtracking step until the camera which has the intersection exists between the third wireless fidelity media access control information set recorded in the target field and the first wireless fidelity media access control information set of one entry record in the matched entry records is found, namely the target camera, or all cameras which pass by the vehicle which is found to be present in the field are found;
when the target camera is found, charging the vehicles which are out of the field according to the entrance time of the entrance records with the intersection;
and when the target camera is not found, prompting to carry out manual charging.
5. The multi-node cooperative vehicle identification method according to any one of claims 1 to 4, wherein the first feature information and the second feature information are semi-structured feature vectors generated by a preset neural network model.
6. A multi-node cooperative vehicle identification apparatus comprising a memory and a processor, the memory storing a program which, when read and executed by the processor, implements the multi-node cooperative vehicle identification method according to any one of claims 1 to 5.
7. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs, the one or more programs being executable by one or more processors to implement the multi-node cooperative vehicle identification method according to any one of claims 1 to 5.
8. A multi-node cooperative vehicle identification system is characterized by comprising a camera positioned at an entrance, a camera positioned at an exit, a camera positioned in a field and a background server, wherein,
the camera at the entrance is configured to acquire a first image of the vehicle when an unlicensed vehicle enters the entrance, or acquire the first image of the vehicle to generate first feature information, and send the first image or the first feature information and the entrance time of the vehicle to the background server; acquiring wireless fidelity media access control information of the vehicle and the periphery, generating a first wireless fidelity media access control information set, and sending the first wireless fidelity media access control information set to the background server;
the camera within the field is configured to capture a third image of the unlicensed vehicle while the unlicensed vehicle is within the field; or acquiring a third image of the unlicensed vehicle to generate third characteristic information, sending the third image or the third characteristic information, acquiring the acquisition time of the third image of the unlicensed vehicle acquired by the cameras in the field to the background server, acquiring the wireless fidelity media access control information of the vehicle and the periphery, generating a third wireless fidelity media access control information set, and sending the third wireless fidelity media access control information set to the background server;
the camera at the exit is configured to acquire a second image of the vehicle when the unlicensed vehicle leaves, or acquire the second image of the vehicle to generate second feature information, send the second image or the second feature information to the background server, and acquire the wireless fidelity media access control information of the vehicle and the periphery to generate a second wireless fidelity media access control information set and send the second wireless fidelity media access control information set to the background server;
the background server is configured to receive a first image sent by a camera at an entrance to generate first feature information, or receive the first feature information sent by the camera at the entrance, receive a first wireless fidelity medium access control information set sent by the camera at the entrance, generate and store an entry record of a vehicle, wherein the entry record comprises identification information allocated to the vehicle, the first feature information, the first wireless fidelity medium access control information set and entry time of the vehicle; receiving a third image sent by a camera in the field to generate third characteristic information, or receiving the third characteristic information sent by the camera in the field; receiving a third wireless fidelity media access control information set sent by cameras in a field, generating and storing a field record of the vehicle, wherein the field record comprises identification information of the cameras in the field, the third characteristic information and the third wireless fidelity media access control information set, and the cameras in the field acquire acquisition time of a third image of the unlicensed vehicle; and receiving a second image sent by the camera at the exit to generate second feature information, or receiving the second feature information sent by the camera at the exit and receiving a second wireless fidelity media access control information set sent by the camera at the exit, and when the second feature information matches a plurality of entry records and the second wireless fidelity media access control information set intersects with a first wireless fidelity media access control information set of more than one entry record in the matched entry records, executing the following backtracking step: calling a history video of a current camera, determining the time when the vehicle on the spot arrives at the current camera from the last camera, and when other vehicles similar to the vehicle on the spot do not exist in the history video, acquiring an on-site record of the last camera within the time period when the vehicle on the spot passes through the last camera, wherein the on-site record is called a target on-site record, and the two-vehicle similarity means that a preset matching condition is met between feature information of the two vehicles; and when the third wireless fidelity media access control information set recorded in the target field is intersected with the first wireless fidelity media access control information set of one of the matched plurality of entrance records, charging the vehicles which come out of the field according to the entrance time of the entrance records with the intersection.
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