Positioning method, storage medium, program product, cloud server and electronic equipment

Abstract

The invention relates to a positioning method, a storage medium, a program product, a cloud server and an electronic device, and relates to the technical field of positioning, the method can comprise the following steps: receiving video data sent by a second device and reference positioning information of the second device; extracting a plurality of key frame images in the video data; acquiring multiple pieces of position feature information according to the reference positioning information; and determining target positioning information corresponding to the second equipment according to the plurality of key frame images and the plurality of pieces of position feature information. Through multi-link matching confirmation, positioning information with higher precision can be obtained, the accuracy of positioning the second equipment is improved, corresponding services can be provided for passengers based on more accurate target positioning information in a subsequent application scene, and the use experience of the passengers is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of positioning technology, and in particular, to a positioning method, a storage medium, a program product, a cloud server, and an electronic device. Background Art

[0002] Mobile taxi services play an important role in the modern transportation field, and more and more people use mobile taxi services to travel. At present, the user's pick-up point in mobile taxi services is mainly determined by mobile phone GPS (Global Positioning System) positioning or by the user manually entering the location.

[0003] However, on the one hand, the accuracy of GPS positioning is not high enough, and large errors will occur in certain environments, affecting the user's taxi experience; on the other hand, the user's manual input of the location is highly dependent on the user's familiarity with the current environment and location. When the user is not familiar with the environment and location, he will not be able to correctly determine the current boarding point. Summary of the invention

[0004] In order to solve the above technical problems, the present disclosure provides a positioning method, a storage medium, a program product, a cloud server and an electronic device.

[0005] In a first aspect, the present disclosure provides a positioning method, applied to a first device, the method comprising: Receiving video data sent by a second device and reference positioning information of the second device; Extracting a plurality of key frame images from the video data; Acquire multiple position feature information according to the reference positioning information; According to the multiple key frame images and the multiple position feature information, target positioning information corresponding to the second device is determined.

[0006] Optionally, the position feature information includes a target positioning image; and acquiring a plurality of position feature information according to the reference positioning information includes: According to the reference positioning information, a plurality of target positioning images are determined from a preset positioning database; wherein the preset positioning database includes a plurality of positioning images.

[0007] Optionally, the preset positioning database further includes image positioning information corresponding to each positioning image, and determining a plurality of target positioning images from the preset positioning database according to the reference positioning information includes: The positioning image in which the image positioning information is located within a first positioning range is used as the target positioning image; wherein the first positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

[0008] Optionally, determining the target positioning information corresponding to the second device according to the multiple key frame images and the multiple position feature information includes: Matching each of the key frame images with the multiple target positioning images, and treating the successfully matched key frame image and the target positioning image as an image pair; The target positioning information is determined according to the image pair.

[0009] Optionally, matching each of the key frame images with the multiple target positioning images includes: Identifying one or more key feature points in each of the key frame images; For each of the key frame images, the key frame image is matched with the multiple target positioning images according to one or more key feature points in the key frame image.

[0010] Optionally, for each of the key frame images, matching the key frame image with the multiple target positioning images according to one or more key feature points in the key frame image includes: For each of the key frame images, if the target positioning image contains the key feature points in the key frame image, it is determined that the target positioning image is successfully matched with the key frame image.

[0011] Optionally, determining the target positioning information according to the image pair includes: For each of the image pairs, determine the relative position information of the key frame image in the image pair relative to the corresponding target positioning image; and determine the pending position corresponding to the key frame image according to the relative position information and the image positioning information corresponding to the target positioning image; The target positioning information is determined according to the undetermined position corresponding to the key frame image in each of the image pairs.

[0012] Optionally, determining the relative position information of the key frame image in the image pair relative to the corresponding target positioning image includes: Mapping the key frame image to the target plane where the corresponding target positioning image is located through affine transformation; Based on the target plane, determining a distance difference between a center point of the key frame image and a center point of the target positioning image; The relative position information of the key frame image in the image pair relative to the corresponding target positioning image is determined according to the distance difference.

[0013] Optionally, in the case of including a plurality of image pairs, determining the target positioning information according to the undetermined position corresponding to the key frame image in each of the image pairs includes: Determine a preset weight corresponding to the target positioning image in each of the image pairs; According to the preset weights, a weighted average value of the plurality of pending positions is determined to obtain the target positioning information.

[0014] Optionally, the location feature information includes target map feature information; and acquiring a plurality of location feature information according to the reference positioning information includes: According to the reference positioning information, multiple target map feature information is determined from a preset high-precision map database; wherein the preset high-precision map database includes multiple map feature information.

[0015] Optionally, the preset high-precision map database also includes map positioning information corresponding to each of the map feature information, and determining a plurality of target map feature information from the preset high-precision map database according to the reference positioning information includes: The map feature information of the map positioning information within a second positioning range is used as the target map feature information; wherein the second positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

[0016] Optionally, determining the target positioning information corresponding to the second device according to the multiple key frame images and the multiple position feature information includes: Performing feature extraction on each of the key frame images to obtain image feature information corresponding to the key frame image; Matching each of the image feature information with the plurality of target map feature information, and treating the successfully matched image feature information and the target map feature information as a feature pair; The target positioning information is determined according to the feature pair.

[0017] Optionally, matching each of the image feature information with the plurality of target map feature information comprises: For each piece of the image feature information, determining a feature similarity between the image feature information and each piece of the target map feature information; When the feature similarity is greater than or equal to a preset similarity threshold, it is determined that the image feature information matches the target map feature information successfully.

[0018] Optionally, the successfully matched image feature information and target map feature information as a feature pair includes: The successfully matched image feature information and the target map feature information are used as a pending feature pair; According to the preset road element features, the feature pair is determined from the plurality of feature pairs to be determined.

[0019] Optionally, the successfully matched image feature information and target map feature information as a feature pair includes: Iterate the steps of matching each of the image feature information with the plurality of target map feature information for multiple times; When the number of iterations reaches a preset number, the successfully matched image feature information and the target map feature information are regarded as a feature pair.

[0020] Optionally, determining the target positioning information according to the feature pair includes: Determine map positioning information corresponding to the target map feature information in the feature pair; The target positioning information is determined according to the map positioning information.

[0021] Optionally, extracting a plurality of key frame images from the video data comprises: Performing preset processing on a plurality of video frame images included in the video data to obtain the plurality of key frame images; The preset processing includes one or more of denoising processing, de-jitter processing and de-duplication processing.

[0022] Optionally, the method further comprises: The target positioning information is sent to a third device.

[0023] In a second aspect, the present disclosure provides a positioning method, applied to a second device, the method comprising: Collecting video data within a target range of an environment where the second device is located; Acquire reference positioning information of the second device when collecting the video data; The video data and the reference positioning information are sent to a first device so that the first device extracts a plurality of key frame images from the video data, obtains a plurality of position feature information based on the reference positioning information, and determines the target positioning information corresponding to the second device based on the plurality of key frame images and the plurality of position feature information.

[0024] In a third aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the positioning method provided in the first aspect of the present disclosure, or implements the steps of the positioning method provided in the second aspect of the present disclosure.

[0025] In a fourth aspect, the present disclosure provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the positioning method provided in the first aspect of the present disclosure, or implements the steps of the positioning method provided in the second aspect of the present disclosure.

[0026] In a fifth aspect, the present disclosure provides a cloud server, comprising: a first memory on which a computer program is stored; and a first processor, configured to execute the computer program in the memory to implement the steps of the positioning method provided in the first aspect of the present disclosure.

[0027] In a sixth aspect, the present disclosure provides an electronic device, comprising: a second memory on which a computer program is stored; and a second processor, configured to execute the computer program in the memory to implement the steps of the positioning method provided in the second aspect of the present disclosure.

[0028] The present disclosure provides a positioning method, first, receiving video data sent by a second device and reference positioning information of the second device; second, extracting multiple key frame images in the video data; then, obtaining multiple position feature information according to the reference positioning information; finally, determining the target positioning information corresponding to the second device according to the multiple key frame images and the multiple position feature information. Through the above method, the second device sends the video data and reference positioning information to the first device, and the first device can obtain multiple position feature information according to the reference positioning information, and obtain the target positioning information corresponding to the second device according to the multiple key frame images and the position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the user experience of passengers.

[0029] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings: Figure 1 The figure is a flowchart of a positioning method according to an exemplary embodiment.

[0031] Figure 2 The figure is a flowchart of a positioning method according to an exemplary embodiment.

[0032] Figure 3The figure is a flowchart of a positioning method according to an exemplary embodiment.

[0033] Figure 4 The figure is a flowchart of a positioning method according to an exemplary embodiment.

[0034] Figure 5 The figure is a flowchart of a positioning method according to an exemplary embodiment.

[0035] Figure 6 The invention is a block diagram of a positioning device according to an exemplary embodiment.

[0036] Figure 7 The invention is a block diagram of a positioning device according to an exemplary embodiment.

[0037] Figure 8 It is a block diagram of an electronic device according to an exemplary embodiment.

[0038] Fig. 9 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0039] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0040] The terms "first", "second", etc. in the specification and claims of this application and the above drawings are used to distinguish similar objects and do not have to be understood as a specific order or sequence. In addition, in the description with reference to the drawings, the same symbols in different drawings represent the same elements.

[0041] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0042] In the description of the present disclosure, unless otherwise specified, "multiple" means two or more than two, and other quantifiers are similar thereto; "at least one item", "one item or multiple items" or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one item a can represent any number of a; for another example, one item or multiple items among a, b and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple; "and / or" is a kind of description of the association relationship of associated objects, indicating that there can be three kinds of relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " indicates that the associated objects before and after are in an "or" relationship.

[0043] Although operations or steps are described in a specific order in the drawings in the embodiments of the present disclosure, it should not be understood that it is required to perform these operations or steps in the specific order shown or in a serial order, or to perform all the operations or steps shown to obtain the desired results. In the embodiments of the present disclosure, these operations or steps can be performed in series; these operations or steps can also be performed in parallel; or some of these operations or steps can be performed.

[0044] Before introducing the positioning method, storage medium, program product, cloud server and electronic device provided by the present disclosure, the application background involved in each embodiment of the present disclosure is first introduced. The present disclosure is applied in the scenario of device positioning. In this scenario, in order to determine the user's boarding point, the device needs to be positioned. At present, it is mainly achieved by mobile phone GPS positioning or by the user manually entering the location. This method depends on the user's current environmental location and the user's familiarity with the location. In addition, this method takes more time to confirm the accuracy of the positioning location for people such as the elderly who are not familiar with the mobile phone operating system, which leads to the following problems: 1. Positioning deviation: GPS positioning will have large errors in certain environments (such as city centers with tall buildings, underground passages, etc.), affecting the user's taxi experience.

[0045] 2. POI (Point of Interest) dependency: Taxi-hailing apps usually automatically match nearby points of interest (POIs), but in some places without obvious POIs, the positioning accuracy is low.

[0046] 3. User confusion: It is difficult for users to determine their own location on two-way roads or in complex environments, especially for users who are not familiar with the location.

[0047] In order to solve the above technical problems, the present invention provides a positioning method, storage medium, program product, cloud server and electronic device. The second device sends video data and reference positioning information to the first device. The first device can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the second device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger experience.

[0048] Secondly, an application scenario to which the present disclosure is applicable is further introduced. The present disclosure can be applied in the scenario of taking a taxi. In this scenario, the passenger needs to send his or her pick-up point to the driver who accepts the order so that the driver can pick up the passenger according to the pick-up point. In the present disclosure, the passenger can collect video data through the second device, and upload the video data and the reference positioning information corresponding to the second device to the first device. The first device determines the target positioning information of the second device based on the video data and the reference positioning information, and can send the target positioning information to the third device. The third device can determine the passenger's pick-up point. At this time, the passenger does not need to upload the location by himself or herself, thereby helping the passenger to achieve a more convenient taxi experience. Among them, the first device can be a cloud server or a vehicle, the second device can be an electronic device held by the passenger, that is, a passenger device, and the third device can be an electronic device held by the driver, that is, a driver device.

[0049] The specific implementation modes of the present invention are described in detail below with reference to the accompanying drawings.

[0050] Figure 1 is a flow chart of a positioning method according to an exemplary embodiment. Figure 1 As shown, applied to a first device, the first device may include a cloud server or a vehicle, and the method may include the following steps: In step S101, video data sent by a second device and reference positioning information of the second device are received.

[0051] In this step, the second device refers to the electronic device held by the passenger, that is, the passenger device. In the scenario of taking a taxi, the passenger can use the second device to shoot the video image of the environment to obtain video data. The reference positioning information is the location information of the passenger when shooting the video data obtained by the positioning device in the second device, for example, it can be GPS positioning information, Beidou satellite positioning information, etc.

[0052] It is understandable that both GPS positioning information and Beidou satellite positioning information have low positioning accuracy, especially in complex urban roads or underground passages, and cannot accurately determine the location of passengers. Therefore, in this embodiment, the location information located by the second device is used as reference positioning information to assist in further determining the location of the second device.

[0053] In step S102, a plurality of key frame images are extracted from the video data.

[0054] For example, a plurality of video frame images included in the video data may be subjected to a preset process to obtain the plurality of key frame images, wherein the preset process includes one or more of a denoising process, a de-jitter process, and a de-duplication process.

[0055] Specifically, the deduplication processing for the multiple video frame images may be performed by determining the corresponding repetition rate for every two video frame images, and when the repetition rate exceeds a preset repetition rate, any one of the video frame images is used as a key frame image.

[0056] In step S103, a plurality of position feature information is acquired according to the reference positioning information.

[0057] In a possible implementation, the location feature information may include a target positioning image. Specifically, multiple target positioning images may be determined from a preset positioning database according to the reference positioning information; wherein the preset positioning database includes multiple positioning images.

[0058] In another possible implementation, the location feature information may include target map feature information. Specifically, multiple target map feature information may be determined from a preset high-precision map database based on the reference positioning information; wherein the preset high-precision map database includes multiple map feature information.

[0059] In step S104, target positioning information corresponding to the second device is determined based on the multiple key frame images and the multiple position feature information.

[0060] In some embodiments, multiple key frame images are matched with multiple position feature information to obtain one or more successfully matched pairs, and target positioning information corresponding to the second device is determined based on the one or more matching pairs.

[0061] For example, when the location feature information includes a target positioning image, the matching pair may include an image pair; when the location feature information includes target map feature information, the matching pair may include a feature pair.

[0062] In addition, after obtaining the target positioning information, the first device can dispatch the order for the passenger and send the target positioning information to the third device of the driver who receives the order, so that the third device can determine the passenger's boarding point according to the received target positioning information, thereby providing the passenger with a ride service. The third device refers to the electronic device held by the driver, that is, the driver's device.

[0063] Through the technical solution provided by the present invention, in a taxi-hailing scenario, the passenger only needs to shoot video data and send the video data and reference positioning information to the first device, and the first device will determine the target positioning information of the second device. The passenger only needs to confirm the get-off point and does not need to determine the boarding point by himself.

[0064] At the same time, considering the elderly and those who are not convenient to operate the second device, quick taxi services can also be provided, and large-font display and voice broadcast functions can be provided. Passengers only need to upload video data. The first device can send the determined target positioning information of the second device to the third device based on the video data and the reference positioning information of the second device. The passenger can provide the driver with the get-off point offline.

[0065] By adopting the above method, the second device sends the video data and reference positioning information to the first device. The first device can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the second device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger experience.

[0066] Figure 2 is a flow chart of a positioning method according to an exemplary embodiment, taking the position feature information including the target positioning image as an example. Figure 2 As shown, the method may include the following steps: In step S201, video data sent by a second device and reference positioning information of the second device are received.

[0067] In step S202, a plurality of key frame images in the video data are extracted.

[0068] For example, a plurality of video frame images included in the video data may be subjected to a preset process to obtain the plurality of key frame images, wherein the preset process includes one or more of a denoising process, a de-jitter process, and a de-duplication process.

[0069] In step S203, a plurality of positioning images of the target are determined from a preset positioning database according to the reference positioning information.

[0070] The preset positioning database includes a plurality of positioning images and image positioning information corresponding to each positioning image.

[0071] For example, a positioning image whose image positioning information is located within a first positioning range may be used as the target positioning image, wherein the first positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

[0072] That is to say, in this step, the target positioning image near the reference positioning information can be screened out from multiple positioning images according to the reference positioning information, so as to facilitate the subsequent determination of the target positioning information where the second device is located according to the target positioning image.

[0073] In step S204, each of the key frame images is matched with the multiple target positioning images, and the key frame image and the target positioning image that are successfully matched are regarded as an image pair.

[0074] In some embodiments, first, one or more key feature points in each of the key frame images may be identified.

[0075] The key feature point may include, for example, a location point where an environmental element contained in the key frame image is located. The environmental element may include, for example, a road sign, a building, a slogan, a road element (such as a lane line, a crosswalk), and the like.

[0076] Secondly, for each of the key frame images, the key frame image may be matched with the multiple target positioning images according to one or more key feature points in the key frame image.

[0077] For example, for each key frame image, if the target positioning image contains the key feature points in the key frame image, it is determined that the target positioning image matches the key frame image successfully, and the successfully matched key frame image and the target positioning image are regarded as an image pair.

[0078] Preferably, when the proportion of key feature points contained in the target positioning image to feature points in the target positioning image is greater than or equal to a preset proportion, it can be determined that the target positioning image matches the key frame image successfully.

[0079] In step S205, the target positioning information is determined according to the image pair.

[0080] In some embodiments, first, for each of the image pairs, relative position information of the key frame image in the image pair relative to the corresponding target positioning image may be determined.

[0081] Specifically, the key frame image can be mapped to the target plane where the corresponding target positioning image is located through an affine transformation. For example, the key frame image can be mapped to the target plane of the target positioning image through an affine transformation matrix. The affine transformation matrix can be, for example, H=findHomography(A, B). Wherein A represents the key frame image, and B represents the target positioning image. Then, based on the target plane, the distance difference between the center point of the key frame image and the center point of the target positioning image can be determined. Thereafter, the relative position information of the key frame image in the image pair relative to the corresponding target positioning image can be determined based on the distance difference.

[0082] In this way, after the relative position information is obtained, the deviation direction and degree of the key frame image and the target positioning image on the same plane can be known, which is convenient for the subsequent determination of the position corresponding to the key frame image.

[0083] Secondly, the pending position corresponding to the key frame image is determined according to the relative position information and the image positioning information corresponding to the target positioning image.

[0084] In this step, the pending position corresponding to the key frame image can be obtained according to the relative position information and the image positioning information corresponding to the target positioning image. In the case of multiple image pairs, the pending position corresponding to the key frame image in each image pair can be determined in turn.

[0085] Finally, the target positioning information is determined according to the undetermined position corresponding to each key frame image in the image pair.

[0086] In the case of including an image pair, the undetermined position corresponding to the key frame image can be directly used as the target positioning information.

[0087] In the case of including multiple image pairs, a first average position of the pending positions corresponding to the key frame images in the multiple image pairs may be determined, and the first average position may be used as the target positioning information.

[0088] In addition, considering that the positioning images stored in the preset positioning database may be different in clarity and reliability, the weight corresponding to each positioning image can be preset. Accordingly, in this step, in the case of multiple image pairs, the preset weight corresponding to the target positioning image in each image pair can be determined. And according to the preset weight, the weighted average of the multiple pending positions is determined to obtain the target positioning information.

[0089] For example, the target positioning information can be determined by the following formula:

[0090] Among them, P is the target positioning information, The preset weight corresponding to each target positioning image, N is the number of image pairs, and Pi is the pending position corresponding to the key frame image.

[0091] By adopting the above method, the second device sends the video data and reference positioning information to the first device. The first device can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the second device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger experience.

[0092] Figure 3 is a flow chart of a positioning method according to an exemplary embodiment, taking the location feature information including the target map feature information as an example. Figure 3 As shown, the method may include the following steps: In step S301, video data sent by a second device and reference positioning information of the second device are received.

[0093] In step S302, a plurality of key frame images in the video data are extracted.

[0094] For example, a plurality of video frame images included in the video data may be subjected to a preset process to obtain the plurality of key frame images, wherein the preset process includes one or more of a denoising process, a de-jitter process, and a de-duplication process.

[0095] In step S303, based on the reference positioning information, multiple target map feature information is determined from a preset high-precision map database.

[0096] The preset high-precision map database includes a plurality of map feature information and map positioning information corresponding to each of the map feature information. At present, high-precision maps often contain a large amount of geographical location information (i.e., map positioning information) and feature information of the map environment (i.e., map features). The map feature information may include, for example, feature information of buildings, roads, signs, and the like. Therefore, in this embodiment, the target positioning information of the second device can be further determined by the high-precision map to improve the accuracy of positioning.

[0097] For example, the map feature information of the map positioning information located within the second positioning range can be used as the target map feature information, wherein the second positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

[0098] That is to say, in this step, target map feature information near the reference positioning information can be screened out from multiple map feature information based on the reference positioning information, so as to facilitate the subsequent determination of the target positioning information where the second device is located based on the target map feature information.

[0099] In step S304, feature extraction is performed on each key frame image to obtain image feature information corresponding to the key frame image.

[0100] For example, a convolutional neural network can be used to extract features from a key frame image to obtain image feature information corresponding to the key frame image. The convolutional neural network can be expressed as F=CNN(I), where I is the key frame image.

[0101] In step S305, each of the image feature information is matched with the plurality of target map feature information, and the successfully matched image feature information and the target map feature information are regarded as a feature pair.

[0102] In some embodiments, first, for each piece of the image feature information, the feature similarity between the image feature information and each piece of the target map feature information may be determined.

[0103] For example, the feature similarity between the image feature information and each target map feature information may be calculated by a similarity function similarity(), wherein the feature information may be a feature vector.

[0104] Then, when the feature similarity is greater than or equal to a preset similarity threshold, it is determined that the image feature information matches the target map feature information successfully, and the successfully matched image feature information and the target map feature information are taken as a feature pair.

[0105] In other embodiments, in order to improve the accuracy of feature pair determination, in a possible implementation, the successfully matched image feature information and the target map feature information can also be used as a pending feature pair, and the feature pair can be determined from a plurality of pending feature pairs according to the preset road element features.

[0106] The road element features are used to characterize the geometric shape of the road elements and / or the road topological relationship. The image feature information in the pending feature pair can be determined by the road element features. For example, the same road extends in the same direction in accordance with the road direction. There is no lane line at the intersection, so there should be no continuous line image feature information. The pending feature pairs containing these image feature information can be discarded to improve the accuracy and reliability of the feature pairs.

[0107] In another possible implementation, the step of matching each image feature information with the plurality of target map feature information may be performed iteratively for multiple times, and when the number of iterations reaches a preset number, the successfully matched image feature information and the target map feature information are regarded as a feature pair.

[0108] In this way, some error feature information can also be filtered out through multiple iterations, and when the number of iterations reaches a preset number, each successfully matched image feature information and the target map feature information after the last matching are taken as a feature pair.

[0109] In step S306, the target positioning information is determined based on the feature pair.

[0110] In some embodiments, the map positioning information corresponding to the target map feature information in the feature pair may be determined, and then the target positioning information is determined based on the map positioning information.

[0111] In the case of including a feature pair, the map positioning information can be directly used as the target positioning information.

[0112] In the case of including multiple feature pairs, a second average position corresponding to the map positioning information in the multiple feature pairs can be determined, and the second average position can be used as the target positioning information.

[0113] For example, the target positioning information can be determined by the following formula:

[0114] Among them, P is the target positioning information, M is the number of feature pairs, Provides location information for the map.

[0115] In addition, after obtaining the target positioning information, in order to further expand the data in the preset positioning database, the successfully matched key frame image can be used as a new positioning image, and the target positioning information corresponding to the key frame image can be stored in the preset positioning database as the image positioning information corresponding to the new positioning image.

[0116] At the same time, the target map feature information in the preset high-precision map database can be updated according to the successfully matched key frame image, the changed map data can be found, and the preset high-precision map database can be updated with the map data in the successfully matched key frame image to further improve the preset high-precision map database.

[0117] In this way, while the embodiments of the present disclosure improve the convenience and experience of passengers' taxi services, as the crowd-source map of intelligent connected vehicles continues to develop, more video data uploaded by users in the future can be used as part of crowd-source data to participate in the construction of high-precision maps, thereby realizing a personal crowd-source data closed loop. Under this taxi solution, the rapid update of high-precision maps can be further supported.

[0118] By adopting the above method, the second device sends the video data and reference positioning information to the first device. The first device can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the second device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger experience.

[0119] Figure 4 is a flowchart of a positioning method according to an exemplary embodiment, which is applied to a second device, such as Figure 4 As shown, the method may include the following steps: In step S401, video data within a target range of the environment where the second device is located is collected.

[0120] In actual application scenarios, it can be independently packaged as an APP or embedded in a general taxi APP. Passengers can call the camera by opening the APP. Passengers only need to use the second device to shoot video images (for example, about 1-2 seconds) within a certain range (for example, 180°) of the current position. For example, the passenger can start from 90° to the left of the road he is facing, offset to the right, and shoot a video image with a duration of about 1-2 seconds. Preferably, when shooting video images, passengers can try to shoot areas that contain detailed signs (such as signs, traffic lights, etc.). If the signs in the area where the passenger is located are not obvious, video images related to road elements such as lane lines can also be shot. Afterwards, the shot video image (i.e., video data) and the reference positioning information of the second device when the video image was shot can be uploaded to the first device.

[0121] In step S402, the reference positioning information of the second device when collecting the video data is obtained.

[0122] The reference positioning information is the location information of the passenger when shooting the video data, which is obtained by the positioning device in the second device, for example, it can be GPS positioning information, Beidou satellite positioning information, etc.

[0123] In step S403, the video data and the reference positioning information are sent to the first device, so that the first device extracts multiple key frame images in the video data, and obtains multiple position feature information based on the reference positioning information, and determines the target positioning information corresponding to the second device based on the multiple key frame images and the multiple position feature information.

[0124] In order to improve the efficiency of subsequent data analysis by the first device and reduce the amount of data transmission, in this embodiment, redundant judgment can also be made on the multiple key frame images contained in the video data on the second device side, key frame images with less feature information can be deleted, and the filtered key frame images can be sent to the first device, so that the first device can determine the target positioning information corresponding to the second device based on the filtered multiple key frame images and the multiple position feature information.

[0125] By adopting the above method, the second device sends the video data and reference positioning information to the first device. The first device can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the second device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger experience.

[0126] Considering that in actual application scenarios, the number of images contained in the preset positioning database is often limited, and it is impossible to fully reflect the images of all roads. The preset high-precision map database contains a large amount of map feature information of all roads, which can ensure the integrity of the data. However, precisely because the number of images contained in the preset positioning database is limited, the efficiency of matching with the positioning image in the preset positioning database is higher. Therefore, a positioning method is also proposed in this embodiment, which can first match the positioning image in the preset positioning database, and then match it with the map feature information in the preset high-precision map database when it is determined that the match fails.

[0127] Figure 5 is a flowchart of a positioning method according to an exemplary embodiment, which is illustrated by taking an example that the first device includes a cloud server, the second device includes a passenger device, and the third device includes a driver device. Figure 5 As shown, the method may include the following steps: In step S501, video data sent by a passenger device and reference positioning information of the passenger device are received.

[0128] In step S502, a plurality of key frame images in the video data are extracted.

[0129] In step S503, multiple key frame images are matched with multiple positioning images in a preset positioning database according to the reference positioning information.

[0130] If it is determined that the multiple key frame images are successfully matched with the multiple positioning images in the preset positioning database, step S504 is executed; If it is determined that the multiple key frame images fail to match the multiple positioning images in the preset positioning database, step S506 is executed.

[0131] In step S504, the successfully matched key frame image and the target positioning image are taken as an image pair.

[0132] In step S505, the target positioning information is determined according to the image pair.

[0133] In step S506, feature extraction is performed on each key frame image to obtain image feature information corresponding to the key frame image.

[0134] In step S507, each piece of the image feature information is matched with the plurality of target map feature information.

[0135] If it is determined that the plurality of image feature information is successfully matched with the plurality of target map feature information, step S508 is executed; If it is determined that the matching between the plurality of image feature information and the plurality of target map feature information fails, step S510 is executed.

[0136] In step S508, the successfully matched image feature information and the target map feature information are regarded as a feature pair.

[0137] In some embodiments, the successfully matched image feature information and the target map feature information may be used as a pending feature pair, and the feature pair may be determined from a plurality of pending feature pairs according to preset road element features.

[0138] In other embodiments, the step of matching each image feature information with the plurality of target map feature information may be performed iteratively for multiple times, and when the number of iterations reaches a preset number, the successfully matched image feature information and the target map feature information are regarded as a feature pair.

[0139] In step S509, the target positioning information is determined according to the feature pair.

[0140] In step S510, the reference positioning information is used as the target positioning information.

[0141] If the map feature information in the preset high-precision map data fails to match, in order to ensure the smooth progress of subsequent related services, the reference positioning information can be used as the target positioning information.

[0142] In step S511, the target positioning information is sent to the driver's device.

[0143] Regarding the method in the above embodiment, the specific manner in which each step performs the operation has been described in the relevant Figures 1 to 4 The method is described in detail in the embodiment of FIG. 1 and will not be described in detail here.

[0144] By adopting the above method, the passenger device sends the video data and reference positioning information to the cloud server. The cloud server can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the passenger device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the passenger device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger's experience.

[0145] Figure 6 is a block diagram of a positioning device according to an exemplary embodiment, which is applied to a first device, and the first device may include a cloud server or a vehicle, such as Figure 6 As shown, the device 600 includes: The receiving module 601 is used to receive the video data sent by the second device and the reference positioning information of the second device; An extraction module 602 is used to extract a plurality of key frame images from the video data; A first acquisition module 603 is used to acquire a plurality of position feature information according to the reference positioning information; The positioning module 604 is used to determine the target positioning information corresponding to the second device according to the multiple key frame images and the multiple position feature information.

[0146] Optionally, the position feature information includes a target positioning image; the first acquisition module 603 is used to determine a plurality of target positioning images from a preset positioning database according to the reference positioning information; wherein the preset positioning database includes a plurality of positioning images.

[0147] Optionally, the preset positioning database also includes image positioning information corresponding to each positioning image, and the first acquisition module 603 is used to use the positioning image with the image positioning information within a first positioning range as the target positioning image; wherein the first positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

[0148] Optionally, the positioning module 604 is used to match each of the key frame images with the multiple target positioning images, and regard the successfully matched key frame image and the target positioning image as an image pair; and determine the target positioning information based on the image pair.

[0149] Optionally, the positioning module 604 is used to identify one or more key feature points in each of the key frame images; for each of the key frame images, the key frame image is matched with the multiple target positioning images according to the one or more key feature points in the key frame image.

[0150] Optionally, the positioning module 604 is configured to determine, for each of the key frame images, that the target positioning image successfully matches the key frame image if the target positioning image contains key feature points in the key frame image.

[0151] Optionally, the positioning module 604 is used to determine, for each image pair, the relative position information of the key frame image in the image pair relative to the corresponding target positioning image; and determine the pending position corresponding to the key frame image based on the relative position information and the image positioning information corresponding to the target positioning image; and determine the target positioning information based on the pending position corresponding to the key frame image in each image pair.

[0152] Optionally, the positioning module 604 is used to map the key frame image to a target plane where the corresponding target positioning image is located through affine transformation; based on the target plane, determine the distance difference between the center point of the key frame image and the center point of the target positioning image; and based on the distance difference, determine the relative position information of the key frame image in the image pair relative to the corresponding target positioning image.

[0153] Optionally, in the case of multiple image pairs, the positioning module 604 is used to determine a preset weight corresponding to the target positioning image in each of the image pairs; based on the preset weight, a weighted average of the multiple pending positions is determined to obtain the target positioning information.

[0154] Optionally, the location feature information includes target map feature information; the first acquisition module 603 is used to determine multiple target map feature information from a preset high-precision map database based on the reference positioning information; wherein the preset high-precision map database includes multiple map feature information.

[0155] Optionally, the preset high-precision map database also includes map positioning information corresponding to each map feature information, and the first acquisition module 603 is used to use the map feature information within the second positioning range of the map positioning information as the target map feature information; wherein the second positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

[0156] Optionally, the positioning module 604 is used to extract features from each key frame image to obtain image feature information corresponding to the key frame image; match each image feature information with the multiple target map feature information, and use the successfully matched image feature information and the target map feature information as a feature pair; and determine the target positioning information based on the feature pair.

[0157] Optionally, the positioning module 604 is used to determine, for each image feature information, a feature similarity between the image feature information and each target map feature information; when the feature similarity is greater than or equal to a preset similarity threshold, determine that the image feature information matches the target map feature information successfully.

[0158] Optionally, the positioning module 604 is used to use the successfully matched image feature information and the target map feature information as a pending feature pair; and determine the feature pair from a plurality of the pending feature pairs according to preset road element features.

[0159] Optionally, the positioning module 604 is used to iterate the step of matching each image feature information with the multiple target map feature information for multiple times; when the number of iterations reaches a preset number, the successfully matched image feature information and the target map feature information are regarded as a feature pair.

[0160] Optionally, the positioning module 604 is used to determine the map positioning information corresponding to the target map feature information in the feature pair; and determine the target positioning information according to the map positioning information.

[0161] Optionally, the extraction module 602 is used to perform preset processing on the multiple video frame images included in the video data to obtain the multiple key frame images; wherein the preset processing includes one or more of denoising processing, de-jitter processing and de-duplication processing.

[0162] Optionally, the positioning module 604 is further configured to send the target positioning information to a third device.

[0163] By using the above device, the second device sends the video data and reference positioning information to the first device. The first device can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the second device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger experience.

[0164] Figure 7 is a block diagram of a positioning apparatus according to an exemplary embodiment, which is applied to a second device, such as Figure 7 As shown, the device 700 includes: A collection module 701 is used to collect video data within a target range of the environment where the second device is located; A second acquisition module 702 is used to acquire reference positioning information of the second device when collecting the video data; The sending module 703 is used to send the video data and the reference positioning information to the first device, so that the first device can extract multiple key frame images in the video data, and obtain multiple position feature information based on the reference positioning information, and determine the target positioning information corresponding to the second device based on the multiple key frame images and the multiple position feature information.

[0165] By using the above device, the second device sends the video data and reference positioning information to the first device. The first device can obtain multiple position feature information based on the reference positioning information, and obtain the target positioning information corresponding to the second device based on multiple key frame images and position feature information in the video data. Through multi-link matching confirmation, higher-precision positioning information can be obtained, which improves the accuracy of positioning the second device. In subsequent application scenarios, corresponding services can be provided to passengers based on more accurate target positioning information, which improves the passenger experience.

[0166] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0167] Figure 8 8 is a block diagram of an electronic device 800 according to an exemplary embodiment. For example, the electronic device 800 may be provided as a cloud server or a vehicle. Figure 8The electronic device 800 includes a first processor 822, which may be one or more, and a first memory 832 for storing a computer program executable by the first processor 822. The computer program stored in the first memory 832 may include one or more modules each corresponding to a set of instructions. In addition, the first processor 822 may be configured to execute the computer program to perform the above-mentioned positioning method.

[0168] In addition, the electronic device 800 may further include a power supply component 826 and a first communication component 850, wherein the power supply component 826 may be configured to perform power management of the electronic device 800, and the first communication component 850 may be configured to implement communication of the electronic device 800, for example, wired or wireless communication. In addition, the electronic device 800 may further include a first input / output (I / O) interface 858. The electronic device 800 may operate based on an operating system stored in the first memory 832, such as Windows Server™, Mac OS X™, Unix™, Linux™, etc.

[0169] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned positioning method are implemented. For example, the computer-readable storage medium can be the above-mentioned first memory 832 including program instructions, and the above-mentioned program instructions can be executed by the first processor 822 of the electronic device 800 to complete the above-mentioned positioning method.

[0170] Fig. 9 FIG. 9 is a block diagram of an electronic device 900 according to an exemplary embodiment. Fig. 9 As shown, the electronic device 900 may include: a second processor 901 , a second memory 902 . The electronic device 900 may also include one or more of a multimedia component 903 , a second input / output (I / O) interface 904 , and a second communication component 905 .

[0171] The second processor 901 is used to control the overall operation of the electronic device 900 to complete all or part of the steps in the above-mentioned positioning method. The second memory 902 is used to store various types of data to support the operation of the electronic device 900. These data may include instructions for any application or method used to operate on the electronic device 900, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The second memory 902 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 903 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the second memory 902 or sent through the second communication component 905. The audio component also includes at least one speaker for outputting audio signals. The second input / output interface 904 provides an interface between the second processor 901 and other interface modules, and the above-mentioned other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The second communication component 905 is used for wired or wireless communication between the electronic device 900 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding second communication component 905 may include: Wi-Fi module, Bluetooth module, NFC module.

[0172] In an exemplary embodiment, the electronic device 900 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to perform the above-mentioned positioning method.

[0173] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned positioning method are implemented. For example, the computer-readable storage medium can be the above-mentioned second memory 902 including program instructions, and the above-mentioned program instructions can be executed by the second processor 901 of the electronic device 900 to complete the above-mentioned positioning method.

[0174] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program that can be executed by a processor. When the computer program is executed by the processor, the steps of the above positioning method are implemented.

[0175] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program that can be executed by a processor. When the computer program is executed by the processor, the steps of the above positioning method are implemented.

[0176] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0177] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0178] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A positioning method, characterized in that: Applied to a first device, the method includes: Receiving video data sent by a second device and reference positioning information of the second device; Extracting a plurality of key frame images from the video data; Acquire multiple position feature information according to the reference positioning information; According to the multiple key frame images and the multiple position feature information, target positioning information corresponding to the second device is determined.

2. The method according to claim 1, characterized in that The position feature information includes a target positioning image; and obtaining a plurality of position feature information according to the reference positioning information includes: According to the reference positioning information, a plurality of target positioning images are determined from a preset positioning database; wherein the preset positioning database includes a plurality of positioning images.

3. The method according to claim 2, characterized in that The preset positioning database also includes image positioning information corresponding to each positioning image, and the determining of a plurality of target positioning images from the preset positioning database according to the reference positioning information includes: The positioning image in which the image positioning information is located within a first positioning range is used as the target positioning image; wherein the first positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

4. The method according to claim 2, characterized in that: The determining, according to the multiple key frame images and the multiple position feature information, the target positioning information corresponding to the second device comprises: Matching each of the key frame images with the multiple target positioning images, and treating the successfully matched key frame image and the target positioning image as an image pair; The target positioning information is determined according to the image pair.

5. The method according to claim 4, characterized in that The matching of each of the key frame images with the multiple target positioning images comprises: Identifying one or more key feature points in each of the key frame images; For each of the key frame images, the key frame image is matched with the multiple target positioning images according to one or more key feature points in the key frame image.

6. The method according to claim 5, characterized in that For each of the key frame images, matching the key frame image with the multiple target positioning images according to one or more key feature points in the key frame image includes: For each of the key frame images, if the target positioning image contains the key feature points in the key frame image, it is determined that the target positioning image is successfully matched with the key frame image.

7. The method according to claim 4, characterized in that Determining the target positioning information according to the image pair includes: For each of the image pairs, determine the relative position information of the key frame image in the image pair relative to the corresponding target positioning image; and determine the pending position corresponding to the key frame image according to the relative position information and the image positioning information corresponding to the target positioning image; The target positioning information is determined according to the undetermined position corresponding to the key frame image in each of the image pairs.

8. The method according to claim 7, characterized in that Determining the relative position information of the key frame image in the image pair relative to the corresponding target positioning image includes: Mapping the key frame image to the target plane where the corresponding target positioning image is located through affine transformation; Based on the target plane, determining a distance difference between a center point of the key frame image and a center point of the target positioning image; The relative position information of the key frame image in the image pair relative to the corresponding target positioning image is determined according to the distance difference.

9. The method according to claim 7, characterized in that: In the case of including multiple image pairs, determining the target positioning information according to the undetermined position corresponding to the key frame image in each of the image pairs includes: Determine a preset weight corresponding to the target positioning image in each of the image pairs; According to the preset weights, a weighted average value of the plurality of pending positions is determined to obtain the target positioning information.

10. The method according to claim 1, characterized in that The location feature information includes target map feature information; The acquiring a plurality of position feature information according to the reference positioning information comprises: According to the reference positioning information, multiple target map feature information is determined from a preset high-precision map database; wherein the preset high-precision map database includes multiple map feature information.

11. The method according to claim 10, characterized in that The preset high-precision map database also includes map positioning information corresponding to each of the map feature information, and the determining of a plurality of target map feature information from the preset high-precision map database according to the reference positioning information includes: The map feature information of the map positioning information within a second positioning range is used as the target map feature information; wherein the second positioning range is a positioning range determined with the position corresponding to the reference positioning information as the center.

12. The method according to claim 10, characterized in that The determining, according to the multiple key frame images and the multiple position feature information, the target positioning information corresponding to the second device comprises: Performing feature extraction on each of the key frame images to obtain image feature information corresponding to the key frame image; Matching each of the image feature information with the plurality of target map feature information, and treating the successfully matched image feature information and the target map feature information as a feature pair; The target positioning information is determined according to the feature pair.

13. The method according to claim 12, characterized in that The matching of each of the image feature information with the plurality of target map feature information comprises: For each piece of the image feature information, determining a feature similarity between the image feature information and each piece of the target map feature information; When the feature similarity is greater than or equal to a preset similarity threshold, it is determined that the image feature information matches the target map feature information successfully.

14. The method according to claim 12, characterized in that The successfully matched feature information of the target map and the target map as a feature pair comprises: The successfully matched image feature information and the target map feature information are used as a pending feature pair; According to the preset road element features, the feature pair is determined from the plurality of feature pairs to be determined.

15. The method according to claim 12, characterized in that The successfully matched image feature information and target map feature information are regarded as a feature pair, including: Iterate the steps of matching each of the image feature information with the plurality of target map feature information for multiple times; When the number of iterations reaches a preset number, the successfully matched image feature information and the target map feature information are regarded as a feature pair.

16. The method according to claim 12, characterized in that Determining the target positioning information according to the feature pair includes: Determine map positioning information corresponding to the target map feature information in the feature pair; The target positioning information is determined according to the map positioning information.

17. The method according to claim 1, characterized in that The extracting of a plurality of key frame images from the video data comprises: Performing preset processing on a plurality of video frame images included in the video data to obtain the plurality of key frame images; The preset processing includes one or more of denoising processing, de-jitter processing and de-duplication processing.

18. The method according to any one of claims 1 to 17, characterized in that The method further comprises: The target positioning information is sent to a third device.

19. A positioning method, characterized in that: Applied to the second device, the method includes: Collecting video data within a target range of an environment where the second device is located; Acquire reference positioning information of the second device when collecting the video data; The video data and the reference positioning information are sent to a first device so that the first device extracts a plurality of key frame images from the video data, obtains a plurality of position feature information based on the reference positioning information, and determines the target positioning information corresponding to the second device based on the plurality of key frame images and the plurality of position feature information.

20. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 18, or implements the steps of the method according to claim 19.

21. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 18, or implements the steps of the method according to claim 19.

22. A cloud server, characterized in that: include: a first memory having a computer program stored thereon; A first processor is configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 18.

23. An electronic device, characterized in that: include: a second memory having a computer program stored thereon; A second processor is used to execute the computer program in the memory to implement the steps of any one of the methods of claim 19.

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