WO2022110801A1 - Data processing method and apparatus, electronic device, and storage medium - Google Patents

Abstract

A data processing method and apparatus, an electronic device, and a storage medium. The method comprises: obtaining multiple pieces of data information acquired with respect to a target region, wherein the data information comprises first sensing data and second sensing data (S11); building, according to the first sensing data, a positioning model corresponding to the target region (S12); obtaining, according to the positioning model, physical location information of the first sensing data (S13); and obtaining, according to the physical location information of the first sensing data, physical location information of the second sensing data (S14). The invention can improve the efficiency of data acquisition.

Description

Data processing method and device, electronic device and storage medium

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on the Chinese patent application with the application number of 202011355417.1 and the filing date of November 26, 2020, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is incorporated herein by reference.

technical field

The present disclosure relates to the technical field of computer vision, and in particular, to a data processing method and apparatus, an electronic device, and a storage medium.

Background technique

With the development of science and technology, positioning technology has been applied to many fields, such as: AR (Augmented Reality, augmented reality) equipment, robotics, navigation and other fields. Exemplarily, when people move indoors and outdoors (for example, inside a large shopping mall, on a city road, etc.), they often need to determine their position through positioning and go to a destination through navigation. In order to improve the accuracy of localization results, localization schemes based on various sensing devices have been proposed one after another.

SUMMARY OF THE INVENTION

The present disclosure proposes a data processing method and apparatus, an electronic device and a storage medium for data processing.

According to an aspect of the present disclosure, a data processing method is provided, comprising:

acquiring a plurality of data information collected for the target area, wherein the data information includes first sensing data and second sensing data;

establishing a positioning model corresponding to the target area according to the first sensing data;

obtaining physical location information of the first sensing data according to the positioning model;

According to the physical location information of the first sensing data, the physical location information of the second sensing data is obtained.

In a possible implementation manner, obtaining the physical location information of the second sensing data according to the physical location information of the first sensing data includes:

According to the physical location information of the first sensing data, the physical location information of the second sensing data collected at the same time as the first sensing data is obtained.

In a possible implementation manner, the first sensing data and the second sensing data have timestamp information, and obtaining the first sensing data according to the physical location information of the first sensing data is the same as the first sensing data. The physical location information of the second sensing data collected at the same time as the sensing data, including:

determining the first sensing data and the second sensing data having the same timestamp information;

The physical location information of the first sensing data is used as the physical location information of the second sensing data having the same timestamp information as the first sensing data.

In a possible implementation manner, the timestamp information of the first sensing data and the timestamp information of the second sensing data are determined by the same clock system.

In a possible implementation, the method further includes:

Perform data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set.

In a possible implementation manner, performing data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set, including:

Segmenting the second sensing data with physical location information according to a preset time interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the physical location information of the second sensing data corresponding to the intermediate time, where the intermediate time is the The middle value of the start time and the end time of the second sensor data set.

In a possible implementation manner, performing data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set, including:

Segmenting the second sensing data with physical location information according to a preset position interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the intermediate location information, where the intermediate location information is the first one in the second sensing data set The physical location information of the second sensing data is an intermediate value of the physical location information of the last second sensing data.

According to an aspect of the present disclosure, there is provided a data processing apparatus, comprising:

an acquisition part, configured to acquire a plurality of data information collected for the target area, wherein the data information includes the first sensing data and the second sensing data;

establishing a model part, configured to establish a positioning model corresponding to the target area according to the first sensing data;

a first processing part, configured to obtain physical location information of the first sensing data according to the positioning model;

The second processing part is configured to obtain the physical location information of the second sensing data according to the physical location information of the first sensing data.

In a possible implementation manner, the second processing part is further configured to:

According to the physical location information of the first sensing data, the physical location information of the second sensing data collected at the same time as the first sensing data is obtained.

In a possible implementation manner, the first sensing data and the second sensing data have timestamp information, and the second processing part is further configured to:

determining the first sensing data and the second sensing data having the same timestamp information;

The physical location information of the first sensing data is used as the physical location information of the second sensing data having the same timestamp information as the first sensing data.

In a possible implementation manner, the timestamp information of the first sensing data and the timestamp information of the second sensing data are determined by the same clock system.

In a possible implementation, the apparatus further includes:

The data segmentation part is configured to perform data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set.

In a possible implementation manner, the data segmentation part is further configured as:

Segmenting the second sensing data with physical location information according to a preset time interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the physical location information of the second sensing data corresponding to the intermediate time, where the intermediate time is the The middle value of the start time and the end time of the second sensor data set.

In a possible implementation manner, the data segmentation part is further configured as:

Segmenting the second sensing data with physical location information according to a preset position interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the intermediate location information, where the intermediate location information is the first one in the second sensing data set The physical location information of the second sensing data is an intermediate value of the physical location information of the last second sensing data.

According to an aspect of the present disclosure, there is provided an electronic device, comprising: a processor; a memory configured to store instructions executable by the processor; wherein the processor is configured to invoke the instructions stored in the memory to execute the above method.

According to an aspect of the present disclosure, there is provided a computer-readable storage medium having computer program instructions stored thereon, the computer program instructions implementing the above method when executed by a processor.

According to an aspect of the present disclosure, there is provided a computer program comprising computer readable code, when the computer readable code is executed in an electronic device, a processor in the electronic device executes to implement the above method.

In the embodiment of the present disclosure, a plurality of data information for the target area may be acquired, the data information may include first sensing data and second sensing data, and a positioning corresponding to the target area may be established according to the first sensing data Model. According to the positioning model, the physical position information of the first sensing data can be obtained, and then the physical position information of the second sensing data can be obtained according to the physical position information of the first sensing data. According to the data processing method and device, electronic device, and storage medium provided by the embodiments of the present disclosure, the physical location information of the second sensing data collected at the same time can be determined by the physical location information of the first sensing data, and there is no need to preset data collection Pointing and manually marking the physical location information of the sensor data can improve the efficiency of data collection, and because the physical location information obtained through the positioning model is more accurate, the accuracy of each sensor data obtained can be improved.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings.

Description of drawings

The accompanying drawings, which are incorporated into and constitute a part of this specification, illustrate embodiments consistent with the present disclosure, and together with the description, serve to explain the technical solutions of the present disclosure.

1 shows a flowchart of a data processing method according to an embodiment of the present disclosure;

FIG. 2 shows a schematic diagram of a positioning model according to an embodiment of the present disclosure;

FIG. 3 shows a flowchart of a data processing method according to an embodiment of the present disclosure;

FIG. 4 shows a schematic diagram 1 of an application scenario according to an embodiment of the present disclosure;

FIG. 5 shows a second schematic diagram of an application scenario according to an embodiment of the present disclosure;

FIG. 6 shows a schematic diagram of a data processing method according to an embodiment of the present disclosure;

FIG. 7 shows a schematic diagram of a file display interface for the second sensor data according to an embodiment of the present disclosure;

8 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure;

FIG. 9 shows a block diagram of an electronic device 800 according to an embodiment of the present disclosure;

FIG. 10 shows a block diagram of an electronic device 1900 according to an embodiment of the present disclosure.

Detailed ways

Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures denote elements that have the same or similar functions. While various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

The term "and/or" in this article is only an association relationship to describe the associated objects, indicating that there can be three kinds of relationships, for example, A and/or B, it can mean that A exists alone, A and B exist at the same time, and A and B exist independently B these three cases. In addition, the term "at least one" herein refers to any combination of any one of the plurality or at least two of the plurality, for example, including at least one of A, B, and C, and may mean including from A, B, and C. Any one or more elements selected from the set of B and C.

In addition, in order to better illustrate the present disclosure, numerous specific details are set forth in the following detailed description. It will be understood by those skilled in the art that the present disclosure may be practiced without certain specific details. In some instances, methods, means, components and circuits well known to those skilled in the art have not been described in detail so as not to obscure the subject matter of the present disclosure.

Data collection is the basis of the indoor positioning model. Usually, multiple data collection points are set in advance, sensors are set to collect data on each data collection point, and the physical location information of the data collection point is marked for the collected data. The information data establishes a positioning model, and performs positioning through the established positioning model. However, the way of manually marking the physical locations of the sensors of the data collection points is inefficient for data collection.

In order to solve this technical problem, an embodiment of the present disclosure provides a data processing method, which can synchronously collect multiple data information of a target area, including first sensing data and second sensing data, wherein the first sensing data may be It is used to establish a positioning model. After the positioning model is obtained, each first sensing data can be positioned through the positioning model to obtain the physical location information of each first sensing data, and then the first sensing data and the second sensing data can be obtained according to each first sensing data. The relationship between the sensing data in time, and the physical location information of the first sensing data, to determine the physical location information of the second sensing data, without the need to preset data collection points and manually mark the physical location information of the sensing data, you can Improve the efficiency of data collection.

1 shows a flowchart of a data processing method according to an embodiment of the present disclosure. The data processing method may be executed by an electronic device such as a terminal device or a server. The terminal device may be a user equipment (User Equipment, UE), a mobile device, a user Terminals, terminals, cellular phones, cordless phones, personal digital assistants (PDAs), handheld devices, computing devices, in-vehicle devices, wearable devices, intelligent robots, etc., the method can call the stored in the memory through the processor. computer readable instructions. Alternatively, the method may be performed by a server.

As shown in Figure 1, the data processing method may include:

In step S11, multiple pieces of data information collected for the target area are acquired, the data information including the first sensing data and the second sensing data.

In this embodiment of the present disclosure, the target area is an area to be data collected, and the area may be a building, a venue, or other area. For example, when pre-training a positioning network for locating a shopping mall (the positioning network is a neural network) , the data information of the shopping mall needs to be collected, and the shopping mall is the target area.

The first sensory data may be data that can be used to build a positioning model. Exemplarily, the first sensing data may be collected by at least one first sensing device. Wherein, the first sensing device may be at least one of a video acquisition device, a laser radar device, an infrared device, and an ultrasonic device, and the first sensing data may be at least one of video data, laser data, infrared data, and ultrasonic data. kind.

It should be noted that, the number of first sensing data included in the data information may be one or more. Exemplarily, one first sensing device may collect one or more pieces of first sensing data, which is not limited in this embodiment of the present disclosure.

The second sensing data is data for which physical location information cannot be directly obtained. Exemplarily, the second sensing data may be collected by at least one second sensing device. The second sensing device may include at least one of a wireless broadband WIFI device, a Bluetooth device, and an Ultra Wide Band (UWB) device, and the second sensing data may include WiFi signals, Bluetooth signals, and UWB data. at least one of.

It should be noted that, the number of second sensing data included in the data information may be one or more. Exemplarily, a second sensing device may collect one or more second sensing data, which is not limited in this embodiment of the present disclosure.

In the embodiment of the present disclosure, at least one first sensing device and at least one second sensing device may be located at the same position in the target area, and collect data information of the target area.

In step S12, a positioning model corresponding to the target area is established according to the first sensing data.

In the embodiment of the present disclosure, taking the first sensing device as a video acquisition device and the first sensing data as video data as an example, after obtaining the first sensing data, a three-dimensional reconstruction method ( For example: SFM (Structure from motion, motion structure recovery) and other methods), establish a localization model corresponding to the target area. Exemplarily, FIG. 2 shows a positioning model obtained by performing three-dimensional reconstruction of the first sensing data through a three-dimensional reconstruction method.

In the process of establishing the positioning model, the acquired inertial measurement unit (IMU, Inertial measurement unit) data can also be used as constraints to obtain a positioning model with higher accuracy.

In the embodiment of the present disclosure, the number of the first transmission data is multiple. In the process of establishing the positioning model according to the first sensing data, in order to improve the accuracy of the positioning model, the registration transmission data in the multiple first sensing data may be used. Sensing data to build a positioning model. Here, the registered sensor data is data satisfying a preset condition in the first sensor data, and the registered sensor data may be one or more of a plurality of first transmission data.

In some embodiments, the preset condition may be a condition for measuring the data quality of the first sensing data. Exemplarily, when a first sensing data satisfies a preset condition, it can be considered that the quality of the first sensing data is better, that is, the first sensing data can be used to establish a positioning model corresponding to the target area. The first sensing data is determined to be registered sensing data.

In this way, through the registered sensor data in the first sensor data, a positioning model corresponding to the target area can be established.

It should be noted that the above-mentioned first sensing data is video data and a positioning model is established by using the SFM technology, which is only an example of the embodiment of the present disclosure. In fact, the type of the first sensing data in the embodiment of the present disclosure is Without limitation, the method for establishing the positioning model based on the first sensing data is not specifically limited.

In step S13, the physical location information of the first sensing data is obtained according to the positioning model.

In the embodiment of the present disclosure, after a positioning model corresponding to the target area is established, each first sensing data may be positioned based on the positioning model to obtain physical location information of each first sensing data.

Still taking the first sensing device as a video acquisition device and the first sensing data as video data as an example, after a positioning model is established according to the first sensing data (video frames in the video data), the Visual positioning is performed on the sensing data to obtain the positioning result of the first sensing data, that is, the physical position information of the first video data is obtained. Exemplarily, the physical location information of the first video data may be obtained by visual positioning through a VPS (Visual Positioning Service, visual positioning service). In fact, the embodiments of the present disclosure do not specifically limit the visual positioning method, and any visual positioning method can be applied to the embodiments of the present disclosure.

In step S14, the physical location information of the second sensing data is obtained according to the physical location information of the first sensing data.

In the embodiment of the present disclosure, the time correlation between each first sensing data and the second sensing data may be determined, and after obtaining the physical location information of each first sensing data, the physical location corresponding to the first sensing data may be information, as the physical location information of the second sensing data that has a time-related relationship with the first sensing data.

In this way, multiple pieces of data information for the target area can be acquired, the data information can include the first sensing data and the second sensing data, and a positioning model corresponding to the target area can be established according to the first sensing data. According to the positioning model, the physical position information of the first sensing data can be obtained, and then the physical position information of the second sensing data can be obtained according to the physical position information of the first sensing data. According to the data processing method provided by the embodiment of the present disclosure, the physical location information of the second sensor data collected at the same time can be determined by the physical location information of the first sensor data, and there is no need to preset the data collection point and manually mark the sensor data. The physical location information can improve the efficiency of data collection, and because the physical location information obtained through the positioning model is more precise, the accuracy of the acquired sensing data can be improved.

In a possible implementation manner, in the above step S14, the obtaining the physical location information of the second sensing data according to the physical location information of the first sensing data may include:

According to the physical location information of the first sensing data, the physical location information of the second sensing data collected at the same time as the first sensing data is obtained.

In this embodiment of the present disclosure, the second sensing data collected at the same time as the first sensing data may be determined, and then the physical location information of the first sensing data may be used as the second sensing data collected at the same time as the first sensing data. Physical location information of sensor data.

Exemplarily, the user may control the first sensing device and the second sensing device to collect data at the same time, the first sensing device collects the first sensing data 1 at time 1, and collects the first sensing data 2 at time 2, , wherein the first sensory data 1 is data for establishing a positioning model. The second sensing data collects the second sensing data 1 at time 1, and after obtaining the physical location information 1 of the first sensing data 1 according to the positioning model, it can be determined that the physical location information corresponding to the second sensing data 1 is physical Location information 1.

In a possible implementation manner, the first sensing data and the second sensing data have timestamp information. Referring to FIG. 3 , according to the physical location information of the first sensing data, the The physical location information of the second sensing data collected at the same moment of the first sensing data may include:

In step S141, the first sensing data and the second sensing data having the same timestamp information are determined.

In this embodiment of the present disclosure, the first sensing device and the second sensing device may be integrated into the same device, and the first sensing device and the second sensing device may obtain the first sensing device by accessing the first clock system of the device. Timestamp information of the sensing data and timestamp information of the second sensing data. The first clock system is a built-in clock system of the device, and each sensor and each application program can obtain time stamp information by accessing the first clock system. Exemplarily, the first clock system can be implemented by a software program. The present disclosure The embodiment does not specifically limit the implementation of the first clock system.

In a possible implementation manner, the timestamp information of the first sensing data and the timestamp information of the second sensing data are determined by the same clock system.

Exemplarily, refer to the schematic diagram 1 of the application scenario shown in FIG. 4 . The first sensing device may be a camera 41 , the second sensing device may be a Bluetooth device 42 , and the first sensing device and the second sensing device are integrated into the electronic device 40 . The electronic device 40 can control the camera 41 and the Bluetooth device 42 to collect data synchronously, and generate time stamp information through the clock system inside the electronic device 40 , and add the time stamp information to the data collected by the camera 41 and the data collected by the Bluetooth device 42 .

In this embodiment of the present disclosure, the first sensing device and the second sensing device are independent devices. The first sensing device and the second sensing device can be connected to the same data acquisition system. The data acquisition system has a second clock system, and the second clock system can provide standard and reliable time stamp information for the connected sensing devices, which can be realized by a hardware timing module or software. Embodiments of the present disclosure The implementation manner of the second clock system is not limited. Both the first sensing device and the second sensing device can obtain timestamp information of the first sensing data and timestamp information of the second sensing data by accessing the second clock system.

In a possible implementation manner, after the first sensing device and the second sensing device are connected to the data acquisition system, the user can send data synchronously to the first sensing device and the second sensing device through the data acquisition system The collection instruction, the first sensing device can collect the first sensing data in response to the data collection instruction, and access the second clock system when collecting the first sensing data to obtain timestamp information of the first sensing data. The second sensing device may collect the second sensing data in response to the data collection instruction, and access the second clock system when collecting the second sensing data to obtain timestamp information of the second sensing data.

Exemplarily, referring to the second schematic diagram of the application scenario shown in FIG. 5 , the first sensing device may be a digital camera device 51 , and the second sensing device may be a wireless fidelity (Wireless Fidelity, WiFi) device 52 . The digital camera device 51 and the WiFi device 52 can collect data under the control of the smart phone 53 . The smartphone 53 can be connected to the digital camera device 51 and the WiFi device 52 through the network 54. In this way, the smart phone 53 can send the data collection instruction to the digital camera device 51 and the WiFi device 52 through the network 54 . When collecting data, the digital camera device 51 and the WiFi device 52 can access the clock system of the smart phone 53 to obtain time stamp information corresponding to the collected data.

The timestamp information of the first sensing data and the second sensing data can be compared, and the second sensing data that is the same as the timestamp information of each first sensing data can be determined from the second sensing data.

It should be noted that the timestamp information can be accurate to the millisecond level. For example, the timestamp information corresponding to a certain transmission data is "2019:10:23:21:05:45:835".

In step S142, the physical location information of the first sensing data is used as the physical location information of the second sensing data having the same timestamp information as the first sensing data.

In the embodiment of the present disclosure, the first sensing data and the second sensing data collected at the same time are data collected at the same location. Since the physical location information of the first sensing data has been obtained through the positioning model, the first sensing data can be The physical location information of the first sensing data is taken as the physical location information of the second sensing data collected at the same time as the first sensing data (that is, having the same timestamp information), so that the second sensing data with the physical location information is obtained. sensor data.

In a possible implementation, the method may further include:

Perform data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set.

In the embodiment of the present disclosure, the purpose of collecting sensor data is to construct a data set, and the data set is used to establish a sensor positioning model corresponding to the target area. Therefore, after the sensor data with physical location information is obtained, the sensor data can be processed by data segmentation to obtain at least one data set, and then a sensor positioning model can be established according to the at least one data set.

For example, after obtaining the second sensing data with physical location information, data segmentation processing may be performed on the second sensing data with physical location information from the perspective of time and/or space to obtain at least one first sensing data. Two sensor data sets, any one of the second sensor data sets includes at least one second sensor data set. For any second sensing data set, multiple second sensing data in the second sensing data set may be regarded as multiple sensing data collected at a data collection point corresponding to the second sensing data set sense data.

After a plurality of second sensing data sets are obtained, a sensing positioning model of the corresponding sensing device can be established according to the second sensing data sets, so that after the second sensing data is subsequently collected, The sensor data and sensor positioning model are used for positioning operation.

In this way, the data processing method provided by the embodiments of the present disclosure can support mobile continuous collection of sensor data, and automatically segment the continuous data to obtain at least one data set for establishing a positioning model, which saves labor costs and improves data efficiency. collection efficiency.

In a possible implementation manner, performing data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set may include:

Segmenting the second sensing data with physical location information according to a preset time interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the physical location information of the second sensing data corresponding to the intermediate time, where the intermediate time is the The middle value of the start time and the end time of the second sensor data set.

For example, the preset time interval can be a preset value, or the preset time interval can also be determined according to the timestamp information and the preset number of second sensing data sets, for example: the timestamp of the second sensing data The minimum information is 00:00:00, and the maximum is 02:00:00. Assuming that the preset number of second sensing data sets is 60, the preset time interval can be determined to be 2 minutes.

According to the timestamp information of the second sensing data, the second sensing data is segmented once every preset time interval, and at least one second transmission data obtained by each segmenting constitutes a second sensing data set. For example, if the preset time interval is 2 minutes, the timestamp information of the second sensing data is divided into: 00:00:00～00:02:00, 00:02:01～00:04:00, … ..., 01:58:01～02:00:00, that is, the second sensing data whose timestamp information is within 00:00:00～00:02:00 constitutes a second sensing data set, and so on, A plurality of second sensory data sets may be obtained.

For any second sensor data set, the middle time in the second sensor data set may be determined, and the middle time may be the middle value of the start time and the end time of the second sensor data set, for example: the second sensor data set The corresponding start time and end time of the sensory data set are: 00:00:00～00:02:00, and the middle time is 00:01:00. The second sensing data corresponding to the intermediate time can be determined, and the physical location information corresponding to the second sensing data can be used as the location information of the data collection point corresponding to the second sensing data set, and the second sensing data The physical location information corresponding to other second sensing data in the data collection point is updated to the location information of the data collection point, so as to obtain a plurality of second sensor data collected at the data collection point.

By analogy, after the physical location information of each second sensing data set is updated, it is equivalent to obtaining multiple second sensing data sets collected at multiple data collection points, and then the multiple second sensing data sets can be obtained according to the multiple second sensing data sets. Set up the positioning model.

In a possible implementation manner, performing data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set may include:

Segmenting the second sensing data with physical location information according to a preset position interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the intermediate location information, where the intermediate location information is the first one in the second sensing data set The physical location information of the second sensing data is an intermediate value of the physical location information of the last second sensing data.

For example, the preset position interval can be a preset value, or the preset position interval can also be determined according to the physical position information and the preset number of second sensing data sets, for example: all the collected second sensing data The longest distance between them is 120m. Assuming that the preset number of second sensing data sets is 60, the preset time interval can be determined to be 2m.

According to the physical location information of the second sensing data, the second sensing data is segmented once every preset location interval, and at least one second transmission data obtained by each segmenting constitutes a second sensing data set. For example, if the preset position interval is 2m, the second sensing data is divided every 2m, and a plurality of second sensing data obtained by each division forms a second sensing data set, and so on. A plurality of second sensor data sets are obtained.

For any second sensing data set, intermediate location information in the second sensing data set may be determined, and the intermediate location information may be physical location information corresponding to the first second sensing data in the second sensing data set , the middle value of the physical location information corresponding to the last second sensor data, for example: the physical location information of the first second sensor data corresponding to the second sensor data set is (x1, y1), the last The physical location information of the second sensing data is (x2, y2), and the intermediate location information is ((x1+x2)/2, (y1+y2)/2). The intermediate position information can be used as the position information of the data collection point corresponding to the second sensing data set, and the physical position information corresponding to a plurality of second sensing data in the second sensing data can be updated to the data collection point. position information of the point to obtain a plurality of second sensing data collected at the data collection point.

By analogy, after the physical location information of each second sensing data set is updated, it is equivalent to obtaining multiple second sensing data sets collected at multiple data collection points, and then the multiple second sensing data sets can be obtained according to the multiple second sensing data sets. Set up the positioning model.

In this way, the second sensing data set for training the positioning model can be obtained without presetting the data collection point and manually marking the physical location of the sensing data, which can improve the efficiency of data collection and the training accuracy of the positioning model. .

In a possible implementation, the method may further include:

The sensing positioning model is trained by the second sensing data set, and the sensing positioning model is obtained, and the sensing positioning model is used for positioning according to the sensing data collected by the second sensing device.

For example, for any second sensing device, after obtaining multiple second sensing data sets corresponding to the second sensing device, each second sensing data set may be used as sample data, and each second sensing data set may be used as sample data. The physical location information corresponding to the second sensing data in the sensing data set is the labeling information of the sample data, and the sensing positioning model corresponding to the second sensing device is obtained through the training of the second sensing data set. Furthermore, during the positioning process, a corresponding positioning result can be obtained through the sensing positioning model according to the second sensing data collected by the second sensing device.

Exemplarily, after a positioning model is established according to the first sensing data, and a corresponding sensing positioning model is established according to the second sensing data, fusion positioning may be performed subsequently, that is, according to the sensing data collected by the first sensing device and The positioning model obtains the first positioning result, the second positioning result is obtained according to the sensing data collected by the second sensing device and the sensing positioning model, and the first positioning result and the second positioning result are fused to obtain the final positioning result.

Since the sensing data used to train the sensing positioning models of the second sensing devices are collected at the same time, and the physical position information is aligned according to the collection time, the fusion positioning of the sensing positioning models obtained through training can improve the The accuracy of the fusion positioning results is improved to improve the robustness of the positioning service.

In the following, the data processing methods provided by the embodiments of the disclosure are described in conjunction with specific application scenarios.

Specifically, with reference to the schematic flowchart described in FIG. 6 , the data processing method provided by the embodiment of the present disclosure may include the following steps:

Step 1. Collect sensing data through multiple sensing devices.

Here, the data processing device can control different sensing devices to collect data synchronously to obtain sensing data carrying time stamp information;

The sensing data may include first sensing data and second sensing data.

Step 2, using the first sensing data to establish a positioning model.

In this embodiment of the present disclosure, the first sensing data may be image frames in a video. The data processing device uses the SFM technology to reconstruct the three-dimensional model of the plurality of first sensing data to obtain a positioning model.

Step 3: Determine physical location information corresponding to the first sensing data based on the positioning model.

It can be understood that, after constructing the positioning model, the data processing device can obtain the position of the optical center of the image frame, thereby obtaining the physical position information of the image frame (ie, the first sensing data).

Based on the timestamp information of the first sensing data obtained in step 1, the corresponding relationship between time and location can be determined.

Step 4: Based on the timestamp information corresponding to the second sensing data, construct a corresponding relationship between the time and the second sensing data.

Step 5. Obtain second sensing data with physical location information by using the corresponding relationship between time and location and the corresponding relationship between time and second sensing data.

That is, the data processing apparatus determines the first sensing data having the same timestamp information as the second sensing data. The location information of the first sensing data is determined as the location information of the second sensing data, so that the second sensing data having the physical location information is obtained.

Step 6: Perform data segmentation processing on the second sensing data to obtain a plurality of second sensing data sets.

In the implementation of the present disclosure, the data processing apparatus may segment and archive the second sensing data according to time intervals. The second sensing data set is equivalent to obtaining multiple second sensing data sets collected at multiple data collection points, and then a sensing positioning model can be established according to the multiple second sensing data sets.

Referring to FIG. 7 , the data processing apparatus performs data segmentation processing on the second sensing data to obtain a schematic diagram of a file display interface of a plurality of second sensing data sets.

In this way, the sensing data of the sensor positioning model is collected at the same time, and the physical location information is aligned according to the collection time. Therefore, when each sensor positioning model obtained through training is used for fusion positioning, the accuracy of the fusion positioning results can be improved, and the positioning service can be improved. robustness.

It can be understood that the above-mentioned method embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle and logic. Due to space limitations, the present disclosure will not repeat them. Those skilled in the art can understand that, in the above method of the specific embodiment, the specific execution order of each step should be determined by its function and possible internal logic.

In addition, the present disclosure also provides data processing apparatuses, electronic devices, computer-readable storage media, and programs, all of which can be used to implement any data processing method provided by the present disclosure. For the corresponding technical solutions and descriptions, refer to the corresponding records in the Methods section. ,No longer.

FIG. 8 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure. As shown in FIG. 8 , the apparatus includes:

The acquiring part 81 can be configured to acquire a plurality of data information collected for the target area, wherein the data information includes the first sensing data and the second sensing data;

establishing a model part 82, which may be configured to establish a positioning model corresponding to the target area according to the first sensing data;

The first processing part 83 can be configured to obtain the physical location information of the first sensing data according to the positioning model;

The second processing part 84 may be configured to obtain the physical location information of the second sensing data according to the physical location information of the first sensing data.

In this way, multiple pieces of data information for the target area can be acquired, the data information can include the first sensing data and the second sensing data, and a positioning model corresponding to the target area can be established according to the first sensing data. According to the positioning model, the physical position information of the first sensing data can be obtained, and then the physical position information of the second sensing data can be obtained according to the physical position information of the first sensing data. According to the data processing apparatus provided by the embodiments of the present disclosure, the physical location information of the second sensor data collected at the same time can be determined by the physical location information of the first sensor data, and there is no need to preset the data collection point and manually mark the sensor data. The physical location information can improve the efficiency of data collection, and because the physical location information obtained through the positioning model is more precise, the accuracy of the acquired sensing data can be improved.

In a possible implementation manner, the second processing part 84 may also be configured as:

According to the physical location information of the first sensing data, the physical location information of the second sensing data collected at the same time as the first sensing data is obtained.

In a possible implementation manner, the first sensing data and the second sensing data have timestamp information, and the second processing part 84 may be further configured as:

determining the first sensing data and the second sensing data having the same timestamp information;

The physical location information of the first sensing data is used as the physical location information of the second sensing data having the same timestamp information as the first sensing data.

In a possible implementation manner, the timestamp information of the first sensing data and the timestamp information of the second sensing data are determined by the same clock system.

In a possible implementation manner, the apparatus may further include:

The data segmentation part may be configured to perform data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set.

In a possible implementation manner, the data segmentation part may also be configured as:

Segmenting the second sensing data with physical location information according to a preset time interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the physical location information of the second sensing data corresponding to the intermediate time, where the intermediate time is the The middle value of the start time and the end time of the second sensor data set.

In a possible implementation manner, the data segmentation part may also be configured as:

Segmenting the second sensing data with physical location information according to a preset position interval to obtain at least one second sensing data set;

For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the intermediate location information, where the intermediate location information is the first one in the second sensing data set The physical location information of the second sensing data is an intermediate value of the physical location information of the last second sensing data.

In some embodiments, the functions or included parts of the apparatus provided in the embodiments of the present disclosure may be configured to execute the methods described in the above method embodiments, and the specific implementation may refer to the above method embodiments. For brevity, I won't go into details here.

Embodiments of the present disclosure further provide a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the foregoing method is implemented. The computer-readable storage medium may be a non-volatile computer-readable storage medium.

An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory that can be configured to store instructions executable by the processor; wherein the processor is configured to call the instructions stored in the memory to execute the above method .

Embodiments of the present disclosure also provide a computer program product, including computer-readable code, when the computer-readable code is run on a device, a processor in the device executes a data processing method configured to implement the data processing method provided in any of the above embodiments instruction.

Embodiments of the present disclosure further provide another computer program product configured to store computer-readable instructions, which, when executed, cause the computer to perform the operations of the data processing method provided by any of the foregoing embodiments.

The electronic device may be provided as a terminal, server or other form of device.

FIG. 9 shows a block diagram of an electronic device 800 according to an embodiment of the present disclosure. For example, electronic device 800 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc. terminal.

9, an electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814 , and the communication component 816 .

The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 can include one or more processors 820 to execute instructions to perform all or some of the steps of the methods described above. Additionally, processing component 802 may include one or more modules that facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

Memory 804 is configured to store various types of data to support operation at electronic device 800 . Examples of such data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, and the like. Memory 804 may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Magnetic or Optical Disk.

Power supply assembly 806 provides power to various components of electronic device 800 . Power supply components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800 .

Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touch, swipe, and gestures on the touch panel. The touch sensor may not only sense the boundaries of a touch or swipe action, but also detect the duration and pressure associated with the touch or swipe action. In some embodiments, the multimedia component 808 includes a front-facing camera and/or a rear-facing camera. When the electronic device 800 is in an operation mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each of the front and rear cameras can be a fixed optical lens system or have focal length and optical zoom capability.

Audio component 810 is configured to output and/or input audio signals. For example, audio component 810 includes a microphone (MIC) that is configured to receive external audio signals when electronic device 800 is in operating modes, such as calling mode, recording mode, and voice recognition mode. The received audio signal may be further stored in memory 804 or transmitted via communication component 816 . In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and a peripheral interface module, which may be a keyboard, a click wheel, a button, or the like. These buttons may include, but are not limited to: home button, volume buttons, start button, and lock button.

Sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of electronic device 800 . For example, the sensor assembly 814 can detect the on/off state of the electronic device 800, the relative positioning of the components, such as the display and the keypad of the electronic device 800, the sensor assembly 814 can also detect the electronic device 800 or one of the electronic device 800 Changes in the position of components, presence or absence of user contact with the electronic device 800 , orientation or acceleration/deceleration of the electronic device 800 and changes in the temperature of the electronic device 800 . Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact. Sensor assembly 814 may also include a light sensor, such as a complementary metal oxide semiconductor (CMOS) or charge coupled device (CCD) image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as wireless network (WiFi), second generation mobile communication technology (2G) or third generation mobile communication technology (3G), or a combination thereof. In one exemplary embodiment, the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

In an exemplary embodiment, electronic device 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable A programmed gate array (FPGA), controller, microcontroller, microprocessor or other electronic component implementation is used to perform the above method.

In an exemplary embodiment, a non-volatile computer-readable storage medium, such as a memory 804 comprising computer program instructions executable by the processor 820 of the electronic device 800 to perform the above method is also provided.

FIG. 10 shows a block diagram of an electronic device 1900 according to an embodiment of the present disclosure. For example, the electronic device 1900 may be provided as a server. 10, electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource, represented by memory 1932, for storing instructions executable by processing component 1922, such as applications. An application program stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Additionally, the processing component 1922 is configured to execute instructions to perform the above-described methods.

The electronic device 1900 may also include a power supply assembly 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input output (I/O) interface 1958 . The electronic device 1900 can operate based on an operating system stored in the memory 1932, such as a Microsoft server operating system (Windows ServerTM), a graphical user interface based operating system (Mac OS XTM) introduced by Apple, a multi-user, multi-process computer operating system (UnixTM). ), Free and Open Source Unix-like Operating System (LinuxTM), Open Source Unix-like Operating System (FreeBSDTM) or similar.

In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as memory 1932 comprising computer program instructions executable by processing component 1922 of electronic device 1900 to perform the above-described method.

The present disclosure may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of the present disclosure.

A computer-readable storage medium may be a tangible device that can hold and store instructions for use by the instruction execution device. The computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of computer readable storage media include: portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM) or flash memory), static random access memory (SRAM), portable compact disk read only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically coded devices, such as printers with instructions stored thereon Hole cards or raised structures in grooves, and any suitable combination of the above. Computer-readable storage media, as used herein, are not to be construed as transient signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (eg, light pulses through fiber optic cables), or through electrical wires transmitted electrical signals.

An embodiment of the present disclosure further provides a computer program, including computer-readable code, when the computer-readable code is executed in an electronic device, a processor in the electronic device executes a state detection method configured to implement the above-mentioned camera lens Example steps.

The computer readable program instructions described herein may be downloaded to various computing/processing devices from a computer readable storage medium, or to an external computer or external storage device over a network such as the Internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer-readable program instructions from a network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing/processing device .

Computer program instructions for carrying out operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or instructions in one or more programming languages. Source or object code, written in any combination, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as the "C" language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server implement. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (eg, using an Internet service provider through the Internet connect). In some embodiments, custom electronic circuits, such as programmable logic circuits, field programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), can be personalized by utilizing state information of computer readable program instructions. Computer readable program instructions are executed to implement various aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer or other programmable data processing apparatus to produce a machine that causes the instructions when executed by the processor of the computer or other programmable data processing apparatus , resulting in means for implementing the functions/acts specified in one or more blocks of the flowchart and/or block diagrams. These computer readable program instructions can also be stored in a computer readable storage medium, these instructions cause a computer, programmable data processing apparatus and/or other equipment to operate in a specific manner, so that the computer readable medium on which the instructions are stored includes An article of manufacture comprising instructions for implementing various aspects of the functions/acts specified in one or more blocks of the flowchart and/or block diagrams.

Computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other equipment to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other equipment to produce a computer-implemented process , thereby causing instructions executing on a computer, other programmable data processing apparatus, or other device to implement the functions/acts specified in one or more blocks of the flowcharts and/or block diagrams.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more functions for implementing the specified logical function(s) executable instructions. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented in dedicated hardware-based systems that perform the specified functions or actions , or can be implemented in a combination of dedicated hardware and computer instructions.

The computer program product can be specifically implemented by hardware, software or a combination thereof. In an optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK), etc. Wait.

Various embodiments of the present disclosure have been described above, and the foregoing descriptions are exemplary, not exhaustive, and not limiting of the disclosed embodiments. Numerous modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the various embodiments, the practical application or improvement over the technology in the marketplace, or to enable others of ordinary skill in the art to understand the various embodiments disclosed herein.

Claims (17)

A data processing method comprising: acquiring a plurality of data information collected for the target area, wherein the data information includes first sensing data and second sensing data; establishing a positioning model corresponding to the target area according to the first sensing data; obtaining physical location information of the first sensing data according to the positioning model; According to the physical location information of the first sensing data, the physical location information of the second sensing data is obtained. The method according to claim 1, wherein the obtaining the physical location information of the second sensing data according to the physical location information of the first sensing data comprises: According to the physical location information of the first sensing data, the physical location information of the second sensing data collected at the same time as the first sensing data is obtained. The method according to claim 2, wherein the first sensing data and the second sensing data have time stamp information, and the obtaining and the The physical location information of the second sensing data collected at the same time as the first sensing data includes: determining the first sensing data and the second sensing data having the same timestamp information; The physical location information of the first sensing data is used as the physical location information of the second sensing data having the same timestamp information as the first sensing data. The method according to claim 3, wherein the time stamp information of the first sensing data and the time stamp information of the second sensing data are determined by the same clock system. The method of any one of claims 1 to 4, wherein the method further comprises: Perform data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set. The method according to claim 5, wherein, performing data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set, comprising: Segmenting the second sensing data with physical location information according to a preset time interval to obtain at least one second sensing data set; For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the physical location information of the second sensing data corresponding to the intermediate time, where the intermediate time is the The middle value of the start time and the end time of the second sensor data set. The method according to claim 5, wherein, performing data segmentation processing on the second sensing data with physical location information to obtain at least one second sensing data set, comprising: Segmenting the second sensing data with physical location information according to a preset position interval to obtain at least one second sensing data set; For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the intermediate location information, where the intermediate location information is the first one in the second sensing data set The physical location information of the second sensing data is an intermediate value of the physical location information of the last second sensing data. A data processing device, comprising: an acquisition part, configured to acquire a plurality of data information collected for the target area, wherein the data information includes the first sensing data and the second sensing data; establishing a model part, configured to establish a positioning model corresponding to the target area according to the first sensing data; a first processing part, configured to obtain physical location information of the first sensing data according to the positioning model; The second processing part is configured to obtain the physical location information of the second sensing data according to the physical location information of the first sensing data. The device according to claim 8, wherein the second processing part is further configured to obtain a second sensor data collected at the same time as the first sensor data according to the physical location information of the first sensor data. Physical location information of sensor data. The apparatus according to claim 9, wherein the second processing part is further configured to determine the first sensing data and the second sensing data having the same time stamp information; The physical location information is used as the physical location information of the second sensing data having the same timestamp information as the first sensing data. The apparatus according to claim 9, wherein the time stamp information of the first sensing data and the time stamp information of the second sensing data are determined by the same clock system. The device according to any one of claims 8 to 11, wherein the data processing device further comprises a data segmentation part, configured to perform data segmentation processing on the second sensing data with physical location information to obtain at least A second sensory dataset. The apparatus according to claim 12, wherein the data segmentation part is further configured to segment the second sensing data with physical location information according to a preset time interval to obtain at least one second sensing data set; For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the physical location information of the second sensing data corresponding to the intermediate time, where the intermediate time is the The middle value of the start time and the end time of the second sensor data set. The device according to claim 12, wherein the data segmentation part is further configured to segment the second sensing data with physical location information according to a preset location interval to obtain at least one second sensing data set; For any second sensing data set, update the physical location information of the second sensing data in the second sensing data set according to the intermediate location information, where the intermediate location information is the first one in the second sensing data set The physical location information of the second sensing data is an intermediate value of the physical location information of the last second sensing data. An electronic device comprising: processor; memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the method of any one of claims 1-7. A computer-readable storage medium having computer program instructions stored thereon, the computer program instructions implementing the method of any one of claims 1 to 7 when executed by a processor. A computer program comprising computer readable code, when the computer readable code is executed in an electronic device, a processor in the electronic device executes the method for implementing any one of claims 1 to 7.

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