WO2021027944A1

WO2021027944A1 - Position compliance recognition method and apparatus, storage medium and electronic apparatus

Info

Publication number: WO2021027944A1
Application number: PCT/CN2020/109344
Authority: WO
Inventors: 薛舟; 陈子冲
Original assignee: 纳恩博（常州）科技有限公司
Priority date: 2019-08-15
Filing date: 2020-08-14
Publication date: 2021-02-18
Also published as: CN110490127A

Abstract

Provided are a position compliance recognition method and apparatus, a storage medium and an electronic apparatus. The method comprises: collecting an image of a position where a target vehicle is located by means of an image collection device installed on the target vehicle insofar as a parking instruction for indicating that the target vehicle is parked is detected (S202); recognizing a target parking position of the target vehicle according to the image (S204); and determining whether the target parking position is a compliant parking position or not by means of determining whether the target parking position is located in a designated parking area or not (S206). The invention solves the problem in the prior art that whether a parking place of a shared vehicle is appropriate cannot be accurately recognized.

Description

Location compliance identification method and device, storage medium and electronic device

Technical field

The present disclosure relates to the field of data processing technology, and in particular, to a location compliance recognition method and device, storage medium, and electronic device.

Background technique

Currently, shared transportation vehicles circulating in the market generally recognize the stopping position through the Global Positioning System (GPS) or Inertial Measurement Unit (IMU) installed inside. However, the accuracy of this recognition method is not high, and it cannot accurately identify whether the shared vehicle is parked at a suitable place.

Regarding the problem of the inability to accurately identify whether the parking place of a shared vehicle is appropriate in related technologies, there is currently no reasonable solution.

Summary of the invention

The embodiments of the present disclosure provide a location compliance recognition method and device, a storage medium, and an electronic device, so as to at least solve the problem in the related art that it is impossible to accurately recognize whether the parking place of a shared vehicle is appropriate.

According to an embodiment of the present disclosure, there is provided a location compliance recognition method, including: in the case of detecting a parking instruction indicating that a target vehicle has stopped, using an image capture device installed on the target vehicle Collect an image of the location of the target vehicle; identify the target parking location of the target vehicle based on the image; determine whether the target parking location is a compliant parking by judging whether the target parking location is located in a designated parking area position.

Optionally, the recognizing the target parking position of the target vehicle according to the image includes: extracting a first image feature in the image; and inputting the first image feature into a first positioning model to identify the The target docking position.

Optionally, after recognizing the target parking position of the target vehicle according to the image, the method further includes: recognizing environmental parameters of the target parking position according to the image, wherein the environmental parameters include at least one of the following: Whether there are buildings blocking the surrounding area, whether there are public facilities in the surrounding area, and whether it is located within the designated parking area.

Optionally, the determining whether the target parking location is a compliant parking location by determining whether the target parking location is located in a designated parking area includes: when the environmental parameters of the target parking location meet a preset rule Next, determine that the target parking position is located in the designated parking area, and then determine that the target parking position is a compliant parking position; when the environmental parameters of the target parking position do not meet the preset rules, determine the The target parking position is not located in the designated parking area, and it is determined that the target parking position is a non-compliant parking position.

Optionally, after the determining that the target parking position is a non-compliant parking position, the method further includes: performing at least one of the following operations: sending the non-compliant parking position to a server; sending warning information, The warning information is used to prompt that the target parking position is a non-compliant parking position, and/or is used to prompt a designated parking area within a designated range from the target parking position.

Optionally, the collecting an image of the location of the target vehicle through an image acquisition device installed on the target vehicle includes: collecting a video image and/or a photo image of the location of the target vehicle within a predetermined time period, Wherein, the target vehicle includes a shared vehicle.

According to another embodiment of the present disclosure, there is also provided a location compliance recognition method, including: in the case of detecting a parking instruction indicating that the target vehicle has stopped, using an image installed on the target vehicle The collection device collects an image of the location of the target vehicle; sends the image to a server so that the server can recognize the target parking position of the target vehicle according to the image; receives the target returned by the server Parking position; determining whether the target parking position is a compliant parking position by determining whether the target parking position is located in a designated parking area.

According to another embodiment of the present disclosure, there is also provided a location compliance recognition method, including: acquiring an image sent by a target vehicle, where the image is that when the target vehicle detects a stop instruction, An image of the location of the target vehicle collected by the image acquisition device installed on the target vehicle, the parking instruction is used to indicate that the target vehicle has stopped; and the image of the target vehicle is identified The target parking position; the identified target parking position is sent to the target vehicle, so that the target vehicle determines whether the target parking position is a closed area by judging whether the target parking position is located in a designated parking area Regulation docking position.

Optionally, the recognizing the target parking position of the target vehicle according to the image includes: extracting a second image feature in the image; and inputting the second image feature into a second positioning model to identify the The target docking position.

According to another embodiment of the present disclosure, there is also provided a location compliance recognition device, including: a first collection module, configured to pass the said stop instruction when the stop instruction indicating that the target vehicle has stopped is detected The image acquisition device installed on the target vehicle collects an image of the location of the target vehicle; the first recognition module is used to identify the target parking position of the target vehicle according to the image; the first determination module is used to pass Determine whether the target parking position is located in a designated parking area, and determine whether the target parking position is a compliant parking position.

Optionally, the recognition module includes: a first extraction unit for extracting a first image feature in the image; a first input unit for inputting the first image feature into a first positioning model to identify The target docking position.

Optionally, the device further includes: a third recognition module for recognizing environmental parameters of the target parking position according to the image, wherein the environmental parameters include at least one of the following: whether there are buildings around, Whether there are public facilities in the surrounding area and whether they are located within the designated stopping area.

Optionally, the first determination module is configured to determine that the target parking position is located in the designated parking area when the environmental parameters of the target parking position meet a preset rule, and then determine the target The parking location is a compliant parking location; when the environmental parameters of the target parking location do not meet the preset rules, it is determined that the target parking location is not located in the designated parking area, and then the target parking location is determined to be Non-compliant docking location.

Optionally, the device further includes: an execution module, configured to perform at least one of the following operations after determining that the target parking position is a non-compliant parking position: sending the non-compliant parking position to Server; sending warning information, wherein the warning information is used to prompt that the target parking location is a non-compliant parking location, and/or used to prompt a designated parking area within a specified range from the target parking location.

Optionally, the first collection module includes: a collection unit configured to collect a video image and/or a photo image of the location of the target vehicle within a predetermined period of time, wherein the target vehicle includes a shared vehicle.

According to another embodiment of the present disclosure, there is also provided a location compliance recognition device, including: a second acquisition module, configured to pass the said parking instruction when the parking instruction indicating that the target vehicle has stopped is detected The image acquisition device installed on the target vehicle collects an image of the location of the target vehicle; the first sending module is configured to send the image to the server so that the server can recognize the target vehicle based on the image The receiving module is used to receive the target stopping position returned by the server; the second determining module is used to determine whether the target stopping position is in the designated stopping area by judging whether the target stopping position is Compliant docking position.

According to another embodiment of the present disclosure, there is also provided a location compliance recognition device, including: an acquisition module, configured to acquire an image sent by a target vehicle, wherein the image shows that the target vehicle detects a stop In the case of an instruction, an image of the location of the target vehicle collected by an image acquisition device installed on the target vehicle, the parking instruction is used to indicate that the target vehicle has stopped; the second recognition module uses To identify the target parking position of the target vehicle according to the image; the second sending module is used to send the identified target parking position to the target vehicle so that the target vehicle can pass the judgment station Whether the target parking position is located in a designated parking area is used to determine whether the target parking position is a compliant parking position.

Optionally, the second recognition module includes: a second extraction unit for extracting a second image feature in the image; a second input unit for inputting the second image feature into a second positioning model, To identify the target docking position.

According to another embodiment of the present disclosure, there is also provided a computer-readable storage medium in which a computer program is stored, wherein the computer program is configured to execute any of the foregoing method embodiments when running A step of.

According to another embodiment of the present disclosure, there is also provided an electronic device including a memory and a processor, the memory is stored with a computer program, and the processor is configured to run the computer program to execute any of the above Steps in the method embodiment.

Through the location compliance recognition method and device, storage medium, and electronic device provided by the embodiments of the present disclosure, in the case of detecting a parking instruction indicating that the target vehicle has stopped, the image acquisition device installed on the target vehicle is used to collect Image of the location of the target vehicle; identify the target parking location of the target vehicle based on the image; determine whether the target parking location is a compliant parking location by judging whether the target parking location is in the designated parking area, that is, through the image that comes with the target vehicle The collection device collects the image of the location and then recognizes it. According to the content displayed in the image, it intuitively determines whether the current parking location meets the rules of the designated parking area, and then determines whether it is a compliant location, which solves the inability to accurately identify shared traffic in the prior art The question of whether the parking place of the tool is appropriate has improved the accuracy of identifying the parking location of shared vehicles.

Description of the drawings

The drawings described here are used to provide a further understanding of the present disclosure and constitute a part of the present application. The exemplary embodiments of the present disclosure and their descriptions are used to explain the present disclosure, and do not constitute an improper limitation of the present disclosure. In the attached picture:

FIG. 1 is a hardware structural block diagram of a mobile terminal of an optional location compliance identification method according to an embodiment of the present disclosure;

2 is a flowchart of an optional location compliance identification method according to an embodiment of the present disclosure;

FIG. 3 is a flowchart of another optional location compliance recognition method according to an embodiment of the present disclosure;

FIG. 4 is a flowchart of another optional location compliance recognition method according to an embodiment of the present disclosure;

FIG. 5 is a flowchart of another optional location compliance recognition method according to an embodiment of the present disclosure;

6 is a structural block diagram of an optional location compliance recognition device according to an embodiment of the present disclosure;

Fig. 7 is a structural block diagram of another optional location compliance recognition device according to an embodiment of the present disclosure;

Fig. 8 is a structural block diagram of another optional location compliance recognition device according to an embodiment of the present disclosure.

detailed description

Hereinafter, the present disclosure will be described in detail with reference to the drawings and in conjunction with embodiments. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other if there is no conflict.

It should be noted that the terms "first" and "second" in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence.

Example 1

The location compliance recognition method embodiment provided in the first embodiment of the present application may be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, FIG. 1 is a hardware structural block diagram of a mobile terminal of a location compliance identification method according to an embodiment of the present disclosure. As shown in FIG. 1, the mobile terminal 10 may include one or more (only one is shown in FIG. 1) processor 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA. ) And a memory 104 for storing data. Optionally, the above mobile terminal may also include a transmission device 106 and an input/output device 108 for communication functions. Those of ordinary skill in the art can understand that the structure shown in FIG. 1 is only for illustration, and does not limit the structure of the above-mentioned mobile terminal. For example, the mobile terminal 10 may also include more or fewer components than those shown in FIG. 1, or have a different configuration from that shown in FIG.

The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as the computer programs corresponding to the method for obtaining scheduling throughput in the embodiments of the present disclosure. The processor 102 runs the computer programs stored in the memory 104, Thereby, various functional applications and data processing are executed, that is, the above-mentioned method is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely provided with respect to the processor 102, and these remote memories may be connected to the mobile terminal 10 via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device 106 is used to receive or send data via a network. The above-mentioned specific example of the network may include a wireless network provided by the communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC for short), which can be connected to other network devices through a base station to communicate with the Internet. In an example, the transmission device 106 may be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet in a wireless manner.

The embodiment of the present disclosure provides a location compliance identification method. FIG. 2 is a flowchart of an optional location compliance identification method according to an embodiment of the present disclosure. As shown in FIG. 2, the method includes:

Step S202, in the case of detecting a parking instruction indicating that the target vehicle has stopped, collect an image of the location of the target vehicle through an image acquisition device installed on the target vehicle;

Step S204: Identify the target stopping position of the target vehicle according to the image;

Step S206: Determine whether the target parking position is a compliant parking position by determining whether the target parking position is located in the designated parking area.

Through the above method, in the case of detecting a parking instruction indicating that the target vehicle has stopped, an image of the location of the target vehicle is collected through the image acquisition device installed on the target vehicle; the target parking of the target vehicle is recognized according to the image Location: Determine whether the target parking location is a compliant parking location by judging whether the target parking location is in the designated parking area, that is, the image of the location is collected by the image capture device of the target vehicle and then recognized, based on the content displayed in the image Intuitively determine whether the current parking location meets the rules of the designated parking area, and then determine whether it is a compliant location, which solves the problem that the existing technology cannot accurately identify whether the parking location of shared vehicles is appropriate, and improves the recognition of the parking location of shared vehicles Accuracy.

Optionally, the target vehicles in the embodiments of the present disclosure may include, but are not limited to, any shared vehicles, for example, shared bicycles, shared cars, shared electric vehicles, shared scooters, and the like.

Optionally, in the case of detecting a parking instruction indicating that the target vehicle has stopped, collecting an image of the location of the target vehicle through an image acquisition device installed on the target vehicle can be achieved through the following steps: After the target vehicle, a parking instruction is triggered. The parking instruction here can be automatically triggered after the user turns off or locks the target vehicle, or it can be triggered by the user. The single-chip microcomputer or chip set inside the target vehicle will trigger the image capture device installed on the target vehicle to take a photo or video after detecting the parking instruction. The lens here can be set as a wide-angle lens or a lens with a deeper depth of field, as much as possible Collect image information of the surrounding environment.

Optionally, recognizing the target stopping position of the target vehicle according to the image can be achieved through the following steps:

S1, extract the first image feature in the image;

S2: Input the first image feature into the first positioning model to identify the target stopping position.

The first positioning model here can be any two classification algorithm model. The input is the sensor data of the target vehicle, including but not limited to the captured image and GPS data of the current stop position, and the output is a determination result between 0 and 1. It should be noted that the result output by the first positioning model can be the identified target stopping position, or the judgment result of whether the target stopping position is located in the designated stopping area, or whether the target stopping position is a compliant stopping position The result of the judgment can also output the probability value of the target parking location in the designated parking area, or the probability value of the target parking location being a compliant parking location, and then judging whether it is a compliant parking location based on the obtained probability value. This is not limited.

The first positioning model here can be implemented by the Support Vector Machine (SVM) algorithm: first prepare training data, that is, known reasonable or unreasonable parking photos and their judgments, and perform features in the image Detection, using detection methods such as harris, DOG, etc., extracting feature description words from feature locations, such as SIFT, Brief, etc., construct a bag of words feature description for each image, and use svm to train regression according to the judgment result Find the correspondence between features and judgments. Every time a new picture is obtained, the picture is first extracted with features, and then the SVM classifier is used to determine whether it is a compliant parking position. The advantage of the Svm algorithm is that the calculation is faster, so it is suitable for running inside the target vehicle, it occupies a small memory, the calculation is fast, and the result can be obtained in time.

Among them, the principle of Harris corner detection is to use a moving window to calculate the gray change value in the image. The key process includes converting to gray image, calculating difference image, Gaussian smoothing, calculating local extremum, and confirming corners. DOG (Difference of Gaussian) is a method of gray image enhancement and corner detection. SIFT, namely Scale-invariant feature transform (SIFT), is a description used in the field of image processing. This description is scale-invariant, can detect key points in the image, and is a local feature descriptor. BRIEF is a 2010 article named "BRIEF: Binary Robust Independent Elementary Features". BRIEF is a description of the detected feature points. It is a binary-coded descriptor that discards the use of regional gray. The traditional method of describing feature points with degree histogram greatly speeds up the establishment of feature descriptors, and also greatly reduces the time for feature matching.

Bag-of-words model (Bag-of-words model) is a simplified expression model under natural language processing and information retrieval (IR). In information retrieval, Bag-of-words model assumes that for a text, its word order, grammar and syntax are ignored , Regard it as just a word set, or a combination of words, the appearance of each word in the text is independent, and it does not depend on whether other words appear or not, or it is not necessary to select a word at any position Selected independently by the influence of the previous sentence.

Bag of words to represent the feature description of the image can be understood in this way. Suppose there are 5 categories of images, and there are 10 images in each category. In this way, each image is first divided into patches (it can be rigid segmentation or it can be based on SIFT key Point detection), in this way, each image is represented by many patches, and each patch is represented by a feature vector. Let's assume that it is represented by Sift. An image may have hundreds of patches, each The dimension of the patch feature vector is 128. Next, build a Bag of words model, assuming that the Size of the Dictionary is 100, that is, there are 100 words. Then you can use the K-means algorithm to cluster all patches, k=100, when k-means converges, get the final centroid of each cluster, then these 100 centroids (dimension 128) are the 100 in the dictionary Words are over, and the dictionary is built. After the dictionary is constructed, first initialize a histogram h of 100 bins with an initial value of 0. There are many patches in each image, calculate the distance between these patches and each centroid again, and see which centroid is closest to each patch, then the corresponding bin in the histogram h is increased by 1, and then the image is calculated. After all the patches, a histogram with bin=100 is obtained, and then normalized, using this 100-dimensional vector to represent the image. After the calculation of all images is completed, classification and clustering training and prediction can be performed.

The first positioning model here can also be implemented by a convolutional neural network. First, prepare the picture and the result of determining whether it is reasonably parked, design the convolutional neural network, such as vgg, resnet, mobilenet, etc., and finally correspond to the features extracted by the network A label head that determines whether parking is reasonable or not, returns a predicted value between 0 and 1.

Since parking reasonable judgment is a classic image classification problem, that is, an image corresponds to a binary classification judgment result of whether or not, there are many other general machine learning methods that can be used for judgment, which is not limited in the embodiment of the present disclosure.

Optionally, recognizing the target parking position of the target vehicle according to the image can also be achieved by the following steps: sending the image to the server, so that the server recognizes the target parking position of the target vehicle in the image.

It should be noted that image recognition can be done in the following three ways:

1. The algorithm a0 deployed in the body of the target vehicle is used to determine whether it is a reasonable parking position, and the determination result d0 is obtained.

2. Upload the image to the cloud server through the wireless network, and determine whether it is a reasonable parking position in the cloud through the algorithm a1, and get the judgment d1.

3. The image is determined by the background user, under the auxiliary information of GPS, through naked eye observation, referring to the preset rules, and the result is d2.

Among them, the algorithm a0 and the algorithm a1 can be implemented by using machine learning algorithms, including the above-mentioned SVM algorithm and convolutional neural network model, which is not limited in the embodiment of the present disclosure. In order to better match the application scenario, the algorithm a0 can choose an algorithm with a fast operation speed and low accuracy requirements, and the algorithm a1 can choose an algorithm with a slower operation speed but higher accuracy.

Different judgment methods can be selected according to the requirements of different business scenarios. For example, when the parking position is unreasonable and the car cannot be returned to the end of the trip, in order to ensure that the judgment result is given quickly, method 1 can be used to make a judgment using the result d0. When the user parks the target vehicle unreasonably one or more times and needs statistical data to decide whether to reduce its credit, he can use the high accuracy but slower method 2 and use the result d1 to make a judgment. When the user thinks that he has parked normally, but is determined to be an unreasonable parking dispute determination, method 3 can be used for manual assistance determination, and the result d2 is used to make the determination.

Among them, the result d2 is generally more accurate, but the quantity is small and the cost is high. The judgment rules need to be judged by experience. For example, the judge must first determine the area where the scooter is parked through GPS, use maps, personal experience, etc., to obtain the judgment basis for normal parking (such as a designated area on the roadside) and abnormal parking in the area, and then use the target vehicle in the image To determine the location.

In the algorithm of method 1 and method 2, the result d2 can be used as the truth value used for verification, and machine learning training can be carried out. Through continuous data accumulation, the accuracy of d0 and d1 can be improved.

There are two results of d0 and d1. Due to different computing resources, d1 may be more accurate than d0. Generally, the results of d0 and d1 are considered at the same time to make judgments. However, when there is network difficulty or large delay, it can only Use the result of d0.

The results of d0 and d1 in the above steps also include the degree of confidence in the judgment. You can decide whether to wait for the result of d1 according to the confidence of d0. When the confidence of d1 is also low, the result d2 can be obtained through manual judgment, which makes it easier to provide machine learning understanding of difficult scenarios.

Optionally, after recognizing the target parking position of the target vehicle according to the image, it further includes: recognizing the environmental parameter of the target parking position according to the image, wherein the environmental parameter includes at least one of the following: whether there is a building block in the surrounding area, and whether there is a surrounding area Whether the public facilities are located in the designated parking area; when the environmental parameters of the target parking location meet the preset rules, it is determined that the standard parking location is located in the designated parking area.

Optionally, the determining whether the target parking position is a compliant parking position by determining whether the target parking position is located in a designated parking area includes: determining whether the environmental parameters of the target parking position meet a preset rule , Determining whether the target parking location is located in the designated parking area; wherein, when the environmental parameters of the target parking location meet a preset rule, it is determined that the target parking location is located in the designated parking area, and then It is determined that the target parking position is a compliant parking position; when the environmental parameters of the target parking position do not meet the preset rules, it is determined that the target parking position is not located in the designated parking area, and then the The target docking position is a non-compliant docking position.

If the surrounding environment is dark and narrow, it may indicate that the parking location is in a relatively hidden place, which is a non-compliant parking location. If the parking area is wide and bright, but there are no public facilities around, it may indicate that the parking location is too remote and it is also an illegal parking location.

The designated stopping area can also be pre-set, and the stopping area can be divided according to GPS data. The stopping area can be set with more eye-catching signs. As long as the target vehicle stops within the designated stopping area, it can be detected by GPS, even if it is not detected, It can also be identified by the logo included in the image.

It should be noted that the warning information can be directly sent by the target vehicle to the user’s client. The client here can be a client used to connect to the target vehicle, or the target vehicle can send the warning information to the server. It is sent by the server to the user's client, which is not limited in the embodiment of the present disclosure.

Optionally, capturing an image of the location of the target vehicle through an image capture device installed on the target vehicle includes: capturing a video image and/or photo image of the location of the target vehicle within a predetermined time period, where the target vehicle includes shared Transportation.

FIG. 3 is a flowchart of an alternative location compliance recognition method according to an embodiment of the present disclosure. As shown in FIG. 3, the method includes:

Step S302, in the case of detecting a parking instruction indicating that the target vehicle has stopped, collect an image of the location of the target vehicle through an image acquisition device installed on the target vehicle;

Step S304: Send the image to the server, so that the server recognizes the target parking position of the target vehicle according to the image;

Step S306, receiving the target parking position returned by the server;

In step S308, it is determined whether the target parking position is a compliant parking position by determining whether the target parking position is located in the designated parking area.

FIG. 4 is a flowchart of another optional location compliance recognition method according to an embodiment of the present disclosure. As shown in FIG. 4, the method includes:

Step S402: Acquire an image sent by the target vehicle, where the image is an image of the location of the target vehicle collected by the image acquisition device installed on the target vehicle when the parking instruction is detected by the target vehicle. When indicating that the target vehicle has stopped;

Step S404: Identify the target stopping position of the target vehicle according to the image;

Step S406: Send the identified target parking location to the target vehicle, so that the target vehicle determines whether the target parking location is a compliant parking location by judging whether the target parking location is located in the designated parking area.

Optionally, recognizing the target stopping position of the target vehicle according to the image includes: extracting a second image feature in the image; and inputting the second image characteristic into a second positioning model to identify the target stopping position. The second positioning model here can use the same algorithm as the first positioning model, and the content already described will not be repeated here. It should be noted that the result output by the second positioning model can be the identified target stopping position, or the judgment result of whether the target stopping position is located in the designated stopping area, or whether the target stopping position is a compliant stopping position The result of the judgment, that is, the image recognition process and the judgment process of the compliant parking position can be executed on the server side, which is not limited in the embodiment of the present disclosure. If the output result of the second positioning model is "the judgment result of whether the target stopping position is located in the designated stopping area", the result is directly sent to the target vehicle, if the output result of the second positioning model is "whether the target stopping position is a compliant stopping position The result of the judgment", directly send this result to the target vehicle, the second positioning model can also output the probability value of the target stopping position in the designated stopping area, or the probability value of the target stopping position being a compliant stopping position, and then output the probability Send the value to the target vehicle.

In order to better understand the interaction process between the target vehicle and the server, a detailed description is given in conjunction with FIG. 5. Fig. 5 is a flowchart of another optional location compliance recognition method according to an embodiment of the present disclosure. As shown in Fig. 5, the method includes:

S501, the user 50 triggers a parking instruction for the target vehicle 52;

S502: After receiving the parking instruction, the target vehicle 52 uses its own installed image acquisition device to collect an image of the location of the target vehicle;

S503: The target vehicle 52 sends the image to the server 54;

S504: The server 54 recognizes the target stopping position of the target vehicle 52 according to the image;

S505: The server 54 sends the identified target stopping position to the target vehicle 52;

S506: The target vehicle 52 determines whether the target parking position is a compliant parking position by judging whether the target parking position is located in the designated parking area;

S507: After the target vehicle 52 recognizes the result, it can give the user 50 a feedback. If it is a compliant parking location, execute the parking instruction, complete the parking and end the use process of the target vehicle, if it is a non-compliant parking location, no The execution of the parking instruction does not end the use process of the target vehicle, and can send a prompt message to the user to remind the user that the current parking location is not compliant, and provide a designated parking area nearby.

The embodiments of the present disclosure also provide a location compliance recognition device, which is used to implement the foregoing location compliance recognition method embodiments and preferred implementations, and those that have been described will not be repeated. As used below, the term "module" can implement a combination of software and/or hardware with predetermined functions. Although the devices described in the following embodiments are preferably implemented by software, hardware or a combination of software and hardware is also possible and conceived.

Fig. 6 is a structural block diagram of an optional location compliance recognition device according to an embodiment of the present disclosure. As shown in Fig. 6, the device includes:

The first collection module 602 is configured to collect an image of the location of the target vehicle through an image collection device installed on the target vehicle in the case of detecting a parking instruction indicating that the target vehicle has stopped;

The first recognition module 604 is configured to recognize the target parking position of the target vehicle according to the image;

The first determining module 606 is used to determine whether the target parking position is a compliant parking position by determining whether the target parking position is located in the designated parking area.

Optionally, the first recognition module 604 includes: a first extraction unit for extracting the first image feature in the image; a first input unit for inputting the first image feature into the first positioning model to identify the target stopping position .

Optionally, the first recognition module 604 includes: a sending unit, configured to send the image to the server, so that the server recognizes the target parking position of the target vehicle in the image.

Optionally, the device further includes: a third recognition module for recognizing the environmental parameters of the target parking position according to the image, wherein the environmental parameters include at least one of the following: whether there are buildings obstructing the surrounding area, whether there are public facilities nearby, Whether it is located in the designated parking area; the third determining module is used to determine that the target parking location is located in the designated parking area when the environmental parameters of the target parking location meet the preset rules.

Optionally, the first determining module 606 is further configured to determine that the target parking position is located in the designated parking area when the environmental parameters of the target parking position meet a preset rule, and then determine the target parking position The parking location is a compliant parking location; when the environmental parameters of the target parking location do not meet the preset rules, it is determined that the target parking location is not located in the designated parking area, and then the target parking location is determined to be Non-compliant docking location.

Optionally, the device further includes: an execution module configured to perform at least one of the following operations: sending the non-compliant parking location to the server; sending warning information, wherein the warning information is used to prompt the target The docking position is a non-compliant docking position, and/or used to prompt a designated docking area within a designated range from the target docking position.

Optionally, the first collection module 602 includes: a collection unit configured to collect a video image and/or a photo image of the location of the target vehicle within a predetermined time period, where the target vehicle includes a shared vehicle.

Fig. 7 is a structural block diagram of another optional location compliance recognition device according to an embodiment of the present disclosure. As shown in Fig. 7, the device includes:

The second acquisition module 702 is configured to collect an image of the location of the target vehicle through an image acquisition device installed on the target vehicle in the case of detecting a parking instruction indicating that the target vehicle has stopped;

The first sending module 704 is configured to send the image to the server, so that the server can recognize the target parking position of the target vehicle according to the image;

The receiving module 706 is used to receive the target parking position returned by the server;

The second determining module 708 is used for determining whether the target parking position is a compliant parking position by determining whether the target parking position is located in the designated parking area.

Fig. 8 is a structural block diagram of an optional location compliance recognition device according to an embodiment of the present disclosure. As shown in Fig. 8, the device includes:

The acquisition module 802 is used to acquire the image sent by the target vehicle, where the image is the image of the location of the target vehicle collected by the image acquisition device installed on the target vehicle when the target vehicle detects the parking instruction, The stop instruction is used to indicate that the target vehicle has stopped;

The second recognition module 804 is configured to recognize the target stopping position of the target vehicle according to the image;

The second sending module 806 is configured to send the identified target parking location to the target vehicle, so that the target vehicle determines whether the target parking location is a compliant parking by judging whether the target parking location is in a designated parking area position.

Optionally, the second recognition module 804 includes: a second extraction unit for extracting the second image feature in the image; a second input unit for inputting the second image feature into the second positioning model to identify the target stopping position . The second positioning model here can use the same algorithm as the first positioning model, and the content already described will not be repeated here.

The embodiments of the present disclosure also provide a computer-readable storage medium in which a computer program is stored, wherein the computer program is configured to execute the steps in any one of the foregoing method embodiments when running. Optionally, the computer-readable storage medium is a non-volatile computer-readable storage medium.

Optionally, in this embodiment, the foregoing storage medium may be configured to store a computer program for executing the following steps:

S1, in the case of detecting a parking instruction indicating that the target vehicle has stopped, collect an image of the location of the target vehicle through an image acquisition device installed on the target vehicle;

S2: Identify the target stopping position of the target vehicle according to the image;

S3: Determine whether the target parking position is a compliant parking position by judging whether the target parking position is located in the designated parking area.

Optionally, in this embodiment, the foregoing storage medium may also be configured to store a computer program for executing the following steps:

S11, in the case of detecting a parking instruction indicating that the target vehicle has stopped, collect an image of the location of the target vehicle through an image acquisition device installed on the target vehicle;

S12. Send the image to a server, so that the server recognizes the target parking position of the target vehicle according to the image;

S13, receiving the target parking position returned by the server;

S14: Determine whether the target parking position is a compliant parking position by judging whether the target parking position is located in a designated parking area.

S21: Acquire an image sent by the target vehicle, where the image is an image of the location of the target vehicle collected by an image acquisition device installed on the target vehicle when the target vehicle detects a parking instruction, and the parking instruction is used for Indicate that the target vehicle has stopped;

S22: Identify the target stopping position of the target vehicle according to the image;

S23. Send the identified target parking location to the target vehicle, so that the target vehicle determines whether the target parking location is a compliant parking by judging whether the target parking location is located in a designated parking area. position.

Optionally, in this embodiment, the above-mentioned storage medium may include, but is not limited to: U disk, read-only memory (Read-Only Memory, ROM for short), Random Access Memory (RAM for short), Various media that can store computer programs, such as mobile hard disks, magnetic disks, or optical disks.

An embodiment of the present disclosure also provides an electronic device, including a memory and a processor, the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the foregoing method embodiments.

Optionally, the aforementioned electronic device may further include a transmission device and an input-output device, wherein the transmission device is connected to the aforementioned processor, and the input-output device is connected to the aforementioned processor.

Optionally, in this embodiment, the foregoing processor may be configured to execute the following steps through a computer program:

S12: Send an image to a server, so that the server recognizes the target parking position of the target vehicle according to the image;

S13, receiving the target parking position returned by the server;

S14: Determine whether the target parking position is a compliant parking position by judging whether the target parking position is located in the designated parking area.

S21: Acquire an image sent by the target vehicle, where the image is an image of the location of the target vehicle collected by the image acquisition device installed on the target vehicle when the target vehicle detects the parking instruction, and the parking instruction is used for Indicate that the target vehicle has stopped;

S23: Send the identified target parking location to the target vehicle, so that the target vehicle determines whether the target parking location is a compliant parking location by determining whether the target parking location is located in a designated parking area.

For specific examples in this embodiment, reference may be made to the examples described in the above-mentioned embodiments and alternative implementations, and this embodiment will not be repeated here.

Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present disclosure can be implemented by a general computing device, and they can be concentrated on a single computing device or distributed in a network composed of multiple computing devices. Above, alternatively, they can be implemented with program codes executable by the computing device, so that they can be stored in the storage device for execution by the computing device, and in some cases, can be executed in a different order than here. Perform the steps shown or described, or fabricate them into individual integrated circuit modules, or fabricate multiple modules or steps of them into a single integrated circuit module to achieve. In this way, the present disclosure is not limited to any specific hardware and software combination.

The foregoing descriptions are only preferred embodiments of the present disclosure, and are not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

A location compliance recognition method, characterized in that it includes:

In the case of detecting a parking instruction indicating that the target vehicle has stopped, collecting an image of the location of the target vehicle through an image acquisition device installed on the target vehicle;

Identifying the target parking position of the target vehicle according to the image;

By judging whether the target parking position is located in a designated parking area, it is determined whether the target parking position is a compliant parking position.
The method according to claim 1, wherein the recognizing the target stopping position of the target vehicle according to the image comprises:

Extracting the first image feature in the image;

The first image feature is input into a first positioning model to identify the target stopping position.
The method according to claim 1, characterized in that, after identifying the target parking position of the target vehicle according to the image, the method further comprises:

The environmental parameters of the target parking position are identified according to the image, wherein the environmental parameters include at least one of the following: whether there is a building block in the surrounding area, whether there are public facilities in the surrounding area, and whether it is located within the designated parking area.
The method according to claim 3, wherein the determining whether the target parking position is a compliant parking position by determining whether the target parking position is located in a designated parking area comprises:

When the environmental parameters of the target parking location meet the preset rules, determining that the target parking location is located in the designated parking area, and then determining that the target parking location is a compliant parking location;

When the environmental parameters of the target parking location do not meet the preset rules, it is determined that the target parking location is not located in the designated parking area, and then the target parking location is determined to be a non-compliant parking location.
The method according to claim 4, wherein after the determining that the target parking position is an uncompliant parking position, the method further comprises: performing at least one of the following operations:

Send the non-compliant parking location to the server;

Sending warning information, wherein the warning information is used to prompt that the target parking location is an illegal parking location, and/or used to prompt a designated parking area within a specified range from the target parking location.
The method according to any one of claims 1 to 5, wherein the collecting an image of the location of the target vehicle through an image acquisition device installed on the target vehicle comprises:

Collect a video image and/or a photo image of the location of the target vehicle within a predetermined period of time, where the target vehicle includes a shared vehicle.
A location compliance recognition method, characterized in that it includes:

In the case of detecting a parking instruction indicating that the target vehicle has stopped, collecting an image of the location of the target vehicle through an image acquisition device installed on the target vehicle;

Sending the image to a server, so that the server recognizes the target parking position of the target vehicle according to the image;

Receiving the target parking position returned by the server;

By judging whether the target parking position is located in a designated parking area, it is determined whether the target parking position is a compliant parking position.
A location compliance recognition method, characterized in that it includes:

Acquire an image sent by a target vehicle, where the image is an image of the location of the target vehicle collected by the image acquisition device installed on the target vehicle when the target vehicle detects a stop instruction Image, the parking instruction is used to indicate that the target vehicle has stopped;

Identifying the target parking position of the target vehicle according to the image;

The identified target parking location is sent to the target vehicle, so that the target vehicle determines whether the target parking location is a compliant parking location by determining whether the target parking location is in a designated parking area.
The method according to claim 8, wherein the identifying the target stopping position of the target vehicle according to the image comprises:

Extracting the second image feature in the image;

The second image feature is input into a second positioning model to identify the target stopping position.
A location compliance recognition device, characterized in that it comprises:

The first collection module is configured to collect an image of the location of the target vehicle through an image acquisition device installed on the target vehicle when a parking instruction indicating that the target vehicle has stopped is detected;

The first recognition module is used to recognize the target parking position of the target vehicle according to the image;

The first determining module is configured to determine whether the target parking position is a compliant parking position by judging whether the target parking position is located in a designated parking area.
The device according to claim 10, wherein the identification module comprises:

The first extraction unit is used to extract the first image feature in the image;

The first input unit is used to input the first image feature into a first positioning model to identify the target stopping position.
The device according to claim 10, wherein the device further comprises:

The third recognition module is configured to recognize the environmental parameter of the target parking position according to the image after recognizing the target parking position of the target vehicle according to the image, wherein the environmental parameter includes at least one of the following: Whether there are buildings blocking the surrounding area, whether there are public facilities in the surrounding area, and whether it is located within the designated parking area.
The device according to claim 12, wherein the first determining module is configured to:

When the environmental parameters of the target parking position meet the preset rules, determining that the target parking position is located in the designated parking area, and then determining that the target parking position is a compliant parking position;

When the environmental parameters of the target parking location do not meet the preset rules, it is determined that the target parking location is not located in the designated parking area, and then the target parking location is determined to be a non-compliant parking location.
The device according to claim 13, wherein the device further comprises: an execution module, configured to perform at least one of the following operations after the determination that the target parking position is an illegal parking position:

Send the non-compliant parking location to the server;

Sending warning information, wherein the warning information is used to prompt that the target parking location is an illegal parking location, and/or used to prompt a designated parking area within a specified range from the target parking location.
The device according to any one of claims 10 to 14, wherein the first collection module comprises:

The collection unit is used to collect a video image and/or a photo image of the location of the target vehicle within a predetermined time period, wherein the target vehicle includes a shared vehicle.
A location compliance recognition device, characterized in that it comprises:

The second acquisition module is configured to collect an image of the location of the target vehicle through an image acquisition device installed on the target vehicle in the case of detecting a parking instruction indicating that the target vehicle has stopped;

The first sending module is configured to send the image to a server, so that the server recognizes the target parking position of the target vehicle according to the image;

A receiving module for receiving the target parking position returned by the server;

The second determining module is used to determine whether the target parking position is a compliant parking position by judging whether the target parking position is located in a designated parking area.
A location compliance recognition device, characterized in that it comprises:

An acquisition module for acquiring an image sent by a target vehicle, where the image is the target acquired by an image acquisition device installed on the target vehicle when the target vehicle detects a parking instruction An image of the location of the vehicle, where the parking instruction is used to indicate that the target vehicle has stopped;

The second recognition module is configured to recognize the target parking position of the target vehicle according to the image;

The second sending module is configured to send the identified target parking position to the target vehicle, so that the target vehicle determines the target parking position by judging whether the target parking position is located in a designated parking area Whether it is a compliant docking position.
The device according to claim 17, wherein the second identification module comprises:

The second extraction unit is used to extract the second image feature in the image;

The second input unit is used to input the second image feature into a second positioning model to identify the target stopping position.
A computer-readable storage medium, wherein a computer program is stored in the storage medium, wherein the computer program is set to execute the method described in any one of claims 1 to 9 when running.
An electronic device comprising a memory and a processor, characterized in that a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of claims 1 to 9 The method described.