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CN112461245A - Data processing method and device, electronic equipment and storage medium - Google Patents

Data processing method and device, electronic equipment and storage medium Download PDF

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Publication number
CN112461245A
CN112461245A CN202011355417.1A CN202011355417A CN112461245A CN 112461245 A CN112461245 A CN 112461245A CN 202011355417 A CN202011355417 A CN 202011355417A CN 112461245 A CN112461245 A CN 112461245A
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China
Prior art keywords
sensing data
position information
data
physical position
sensing
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Inventor
张笑宇
焦飞
盛崇山
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Zhejiang Shangtang Technology Development Co Ltd
Zhejiang Sensetime Technology Development Co Ltd
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Zhejiang Shangtang Technology Development Co Ltd
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Priority to CN202011355417.1A priority Critical patent/CN112461245A/en
Publication of CN112461245A publication Critical patent/CN112461245A/en
Priority to PCT/CN2021/103180 priority patent/WO2022110801A1/en
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20Instruments for performing navigational calculations
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/005Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29Geographical information databases

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)
  • Telephone Function (AREA)

Abstract

The present disclosure relates to a data processing method and apparatus, an electronic device, and a storage medium, the method including: acquiring a plurality of pieces of data information acquired aiming at a target area, wherein the data information comprises first sensing data and second sensing data; establishing a positioning model corresponding to the target area according to the first sensing data; obtaining physical position information of the first sensing data according to the positioning model; and obtaining the physical position information of the second sensing data according to the physical position information of the first sensing data. The embodiment of the disclosure can improve the data acquisition efficiency.

Description

Data processing method and device, electronic equipment and storage medium
Technical Field
The present disclosure relates to the field of computer vision technologies, and in particular, to a data processing method and apparatus, an electronic device, and a storage medium.
Background
With the development of technology, positioning technology is applied to many fields, such as: the fields of AR (Augmented Reality) equipment, robots, navigation, and the like. For example, when people move indoors and outdoors (e.g., inside a large mall, on a city road, etc.), people often need to determine their location by positioning and navigate to a destination. In order to improve the accuracy of the positioning result, positioning schemes based on various sensing devices are proposed in succession.
Disclosure of Invention
The present disclosure proposes a data processing solution for data processing.
According to an aspect of the present disclosure, there is provided a data processing method including:
acquiring a plurality of pieces of data information acquired aiming at a target area, wherein the data information comprises first sensing data and second sensing data;
establishing a positioning model corresponding to the target area according to the first sensing data;
obtaining physical position information of the first sensing data according to the positioning model;
and obtaining the physical position information of the second sensing data according to the physical position information of the first sensing data.
In a possible implementation manner, the obtaining the physical location information of the second sensing data according to the physical location information of the first sensing data includes:
and obtaining the physical position information of second sensing data acquired at the same time with the first sensing data according to the physical position information of the first sensing data.
In a possible implementation manner, the obtaining, according to the physical location information of the first sensing data, the physical location information of the second sensing data acquired at the same time as the first sensing data, where the first sensing data and the second sensing data have timestamp information, includes:
determining first sensing data and second sensing data having the same timestamp information;
and taking the physical position information of the first sensing data as the physical position information of second sensing data with the same time stamp information as the first sensing data.
In one 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 one possible implementation, the method further includes:
and carrying out data segmentation processing on the second sensing data with the physical position information to obtain at least one second sensing data set.
In a possible implementation manner, the performing data segmentation processing on the second sensing data with the physical location information to obtain at least one second sensing data set includes:
segmenting second sensing data with physical position information according to a preset time interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to the physical position information of the second sensing data corresponding to the intermediate time, wherein the intermediate time is the intermediate value of the starting time and the ending time of the second sensing data set.
In a possible implementation manner, the performing data segmentation processing on the second sensing data with the physical location information to obtain at least one second sensing data set includes:
segmenting second sensing data with physical position information according to a preset position interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to intermediate position information, wherein the intermediate position information is an intermediate value between the physical position information of the first second sensing data in the second sensing data set and the physical position information of the last second sensing data.
According to an aspect of the present disclosure, there is provided a data processing apparatus including:
the acquisition module is used for acquiring a plurality of data information acquired aiming at a target area, wherein the data information comprises first sensing data and second sensing data;
the model establishing module is used for establishing a positioning model corresponding to the target area according to the first sensing data;
the first processing module is used for obtaining physical position information of the first sensing data according to the positioning model;
and the second processing module is used for obtaining the physical position information of the second sensing data according to the physical position information of the first sensing data.
In a possible implementation manner, the second processing module is further configured to:
and obtaining the physical position information of second sensing data acquired at the same time with the first sensing data according to the physical position information of the first sensing data.
In a possible implementation manner, the first sensing data and the second sensing data have timestamp information, and the second processing module is further configured to:
determining first sensing data and second sensing data having the same timestamp information;
and taking the physical position information of the first sensing data as the physical position information of second sensing data with the same time stamp information as the first sensing data.
In one 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 one possible implementation, the apparatus further includes:
and the data segmentation module is used for carrying out data segmentation processing on the second sensing data with the physical position information to obtain at least one second sensing data set.
In a possible implementation manner, the data slicing module is further configured to:
segmenting second sensing data with physical position information according to a preset time interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to the physical position information of the second sensing data corresponding to the intermediate time, wherein the intermediate time is the intermediate value of the starting time and the ending time of the second sensing data set.
In a possible implementation manner, the data slicing module is further configured to:
segmenting second sensing data with physical position information according to a preset position interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to intermediate position information, wherein the intermediate position information is an intermediate value between the physical position information of the first second sensing data in the second sensing data set and the physical position information of the last second sensing data.
According to an aspect of the present disclosure, there is provided an electronic device including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.
According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method.
In the embodiment of the disclosure, a plurality of data information for a target area may be acquired, where the data information may include first sensing data and second sensing data, and a positioning model corresponding to the target area may 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 further, according to the physical position information of the first sensing data, the physical position information of the second sensing data can be obtained. According to the data processing method and device, the electronic device and the storage medium provided by the embodiment of the disclosure, the physical position information of the second sensing data acquired at the same time can be determined through the physical position information of the first sensing data, the data acquisition efficiency can be improved without presetting a data acquisition point and manually marking the physical position information of the sensing data, and the accuracy of the physical position information obtained through the positioning model is higher because the accuracy of each obtained sensing data can be improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.
FIG. 1 shows a flow diagram of a data processing method according to an embodiment of the present disclosure;
FIG. 2 shows a flow diagram of a data processing method according to an embodiment of the present disclosure;
FIG. 3 shows a schematic diagram of a data processing method according to an embodiment of the present disclosure;
FIG. 4 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure;
FIG. 5 shows a block diagram of an electronic device 800 in accordance with an embodiment of the disclosure;
fig. 6 illustrates a block diagram of an electronic device 1900 in accordance with an embodiment of the disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically 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" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
Data acquisition is the basis of an indoor positioning model, generally, a plurality of data acquisition points are preset, a sensor is arranged on each data acquisition point to acquire data, physical position information of the data acquisition points is marked on the acquired data, a positioning model is established by using the data marked with the physical position information, and positioning is performed through the established positioning model. However, manually marking the physical location of the sensors at the data acquisition site is inefficient in data acquisition.
In order to solve the technical problem, an embodiment of the present disclosure provides a data processing method, which may acquire a plurality of data information of a target area synchronously, where the data information includes first sensing data and second sensing data, where the first sensing data may be used to establish a positioning model, and after the positioning model is obtained, the first sensing data may be positioned through the positioning model to obtain physical location information of each first sensing data, and then the physical location information of the second sensing data may be determined according to a temporal association relationship between each first sensing data and each second sensing data and the physical location information of the first sensing data, and the physical location information of the second sensing data is not required to be preset with a data acquisition point and manually mark the physical location information of the sensing data, so that the efficiency of data acquisition may be improved.
Fig. 1 shows a flowchart of a data processing method according to an embodiment of the present disclosure, which may be performed by an electronic device such as a terminal device or a server, the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like, and the method may be implemented by a processor calling a computer-readable instruction stored in a memory. Alternatively, the method may be performed by a server.
As shown in fig. 1, the data processing method may include:
in step S11, a plurality of pieces of data information collected for the target area are acquired, the data information including the first sensed data and the second sensed data.
In the embodiment of the present disclosure, the target area is an area to be subjected to data acquisition, and the area may be an area of a building, a venue, or the like, for example: when a positioning network (the positioning network is a neural network) for positioning a shopping mall is pre-trained, data information of the shopping mall needs to be collected, and the shopping mall is a target area.
The first sensing data may be data that can be used to build a positioning model, and may be collected by at least one first sensing device, for example: the first sensing device may be at least one of a video acquisition device, a lidar 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, etc.
The second sensing data is data that cannot directly obtain the physical location information, and for example, the second sensing data may be collected by at least one second sensing device, for example: 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 at least one of a WIFI signal, a bluetooth signal, and UWB data.
In the embodiment of the present disclosure, at least one first sensing device and at least one second sensing device are 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 capture device, taking the first sensing data as video data as an example, after the first sensing data is obtained, a positioning model corresponding to the target area may be established according to the first sensing data by using a three-dimensional reconstruction method (for example, SFM (Structure from motion), and the like). In the process of establishing the positioning model, the acquired Inertial Measurement Unit (IMU) data can be used as a constraint to obtain a positioning model with higher precision.
In the embodiment of the disclosure, 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 positioning model may be established by using the registered sensing data in the first sensing data, where the registered sensing data is data that satisfies the preset condition in the first sensing data. The preset condition may be a condition for measuring data quality of the first sensing data, and when the first sensing data meets the preset condition, the first sensing data may be considered to have better quality and may be used to establish a positioning model corresponding to the target area, so that the first sensing data may be determined as the registered sensing data. And establishing a positioning model corresponding to the target area through the registered sensing data in the first sensing data.
It should be noted that the first sensing data is video data and the positioning model is established by using the SFM technology, which is only an example of the embodiment of the present disclosure, and actually, the type of the first sensing data is not limited in the embodiment of the present disclosure, and the establishing manner of the positioning model based on the first sensing data is not specifically limited.
In step S13, physical location information of the first sensing data is obtained according to the positioning model.
In the embodiment of the disclosure, after the positioning model corresponding to the target area is established, the first sensing data may be positioned based on the positioning model, so as to obtain the physical position information of the first sensing data.
Still taking the first sensing device as the video acquisition device and the first sensing data as the video data as an example, after the positioning model is established according to the first sensing data (video frames in the video data), the first sensing data can be visually positioned according to the positioning model to obtain the positioning result of the first sensing data, that is, the physical position information of the first video data is obtained. Illustratively, the physical location information of the first video data may be obtained by VPS (Visual Positioning Service) Visual Positioning. In fact, the embodiment of the present disclosure does not specifically limit the visual positioning manner, and any visual positioning manner can be applied to the embodiment 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, a time association relationship 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 information corresponding to the first sensing data may be used as the physical location information of the second sensing data having a time association relationship with the first sensing data.
In this way, a plurality of data information for the target area may be acquired, where the data information may include the first sensing data and the second sensing data, and a positioning model corresponding to the target area may 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 further, according to the physical position information of the first sensing data, the physical position information of the second sensing data can be obtained. According to the data processing method provided by the embodiment of the disclosure, the physical position information of the second sensing data acquired at the same time can be determined through the physical position information of the first sensing data, the physical position information of the data acquisition point and the sensing data marked manually does not need to be preset, the data acquisition efficiency can be improved, and the accuracy of the physical position information obtained through the positioning model is higher, so that the accuracy of each obtained sensing data can be improved.
In a possible implementation manner, in 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:
and obtaining the physical position information of second sensing data acquired at the same time with the first sensing data according to the physical position information of the first sensing data.
In the embodiment of the present disclosure, the second sensing data acquired 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 physical location information of the second sensing data acquired at the same time as the first sensing data.
For example, the user may control the first sensing device to perform data collection simultaneously with the second sensing device, where the first sensing device collects the first sensing data 1 at time 1 and collects the first sensing data 2 at time 2, … …, where the first sensing data 1 is data used for building the positioning model. The second sensing data 1 is acquired at the moment 1, and after the physical position information 1 of the first sensing data 1 is obtained according to the positioning model, the physical position information corresponding to the second sensing data 1 can be determined to be the physical position information 1.
In a possible implementation manner, the obtaining, according to the physical location information of the first sensing data, the physical location information of the second sensing data acquired at the same time as the first sensing data according to the time stamp information of the first sensing data and the second sensing data may include:
in step S141, the first sensed data and the second sensed data having the same time stamp information are determined.
In the embodiment of the present disclosure, the first sensing device and the second sensing device may be integrated in the same device (for example, the first sensing device is a camera, the second sensing device is a bluetooth device, and the first sensing device and the second sensing device are integrated in a mobile phone), and then the first sensing device and the second sensing device may obtain timestamp information of the first sensing data and timestamp information of the second sensing data by accessing a first clock system of the device, where the first clock system is a clock system of the device itself, and each sensor and each application program may obtain the timestamp information by accessing the first clock system.
In one possible implementation manner, 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.
In the embodiment of the present disclosure, the first sensing device and the second sensing device may access the same data acquisition system, for example: the first sensing equipment is digital camera equipment, the second sensing equipment is a mobile phone, and the first sensing equipment and the second sensing equipment can be connected to the data acquisition system. The data acquisition system is provided with a second clock system, the second clock system can provide standard and reliable timestamp information for the accessed sensing equipment, the timestamp information can be realized through a hardware time service module and also can be realized through software, and the embodiment of the disclosure does not limit the realization mode of the second clock system at all. The first sensing device and the second sensing device can both access the second clock system to obtain the timestamp information of the first sensing data and the timestamp information of the second sensing data.
For example, after the first sensing device and the second sensing device are connected to the data acquisition system, a user may send a data acquisition instruction to the first sensing device and the second sensing device synchronously through the data acquisition system, and the first sensing device may acquire the first sensing data in response to the data acquisition instruction and access the second clock system when acquiring the first sensing data to obtain timestamp information of the first sensing data. The second sensing device may acquire second sensing data in response to the data acquisition instruction and access the second clock system when acquiring the second sensing data to obtain timestamp information of the second sensing data.
The timestamp information of the first sensing data and the timestamp information of the second sensing data can be compared, and the second sensing data which is the same as the timestamp information of each first sensing data can be determined from the second sensing data.
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 acquired at the same time are acquired at the same position, and the physical position information of the first sensing data is already obtained through the positioning model, so that the physical position information of the first sensing data can be used as the physical position information of the second sensing data acquired at the same time (i.e., with the same timestamp information) as the first sensing data, so as to obtain the second sensing data with the physical position information.
In one possible implementation, the method may further include:
and carrying out data segmentation processing on the second sensing data with the physical position information to obtain at least one second sensing data set.
In the embodiment of the present disclosure, the purpose of collecting the sensing data is to construct a data set, where the data set is used to establish a sensing and positioning model corresponding to the target region. Therefore, after the sensing data with the physical position information is obtained, data segmentation processing can be carried out on the sensing data to obtain at least one data set, and then a sensing positioning model is established according to the at least one data set.
For example, referring to fig. 3, after obtaining the second sensing data with physical location information, the second sensing data with physical location information may be subjected to data slicing from a time and/or space perspective to obtain at least one second sensing data set, where any second sensing data set includes at least one second sensing data. For any second sensing data set, a plurality of second sensing data in the second sensing data set can be regarded as a plurality of sensing data acquired at one data acquisition point corresponding to the second sensing data set.
After a plurality of second sensing data sets are obtained, a sensing positioning model of the corresponding sensor can be established according to the second sensing data sets, so that positioning operation can be performed according to the second sensing data and the sensing positioning model after the second sensing data are subsequently acquired.
Therefore, the data processing method provided by the embodiment of the disclosure can support moving continuous acquisition of sensing data, automatically segment the continuous data, and obtain at least one data set for establishing a positioning model, thereby saving labor cost and improving data acquisition efficiency.
In a possible implementation manner, the 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 second sensing data with physical position information according to a preset time interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to the physical position information of the second sensing data corresponding to the intermediate time, wherein the intermediate time is the intermediate value of the starting time and the ending time of the second sensing data set.
For example, the preset time interval may be a preset value, or may also be determined according to the timestamp information and the preset number of the second sensing data sets, for example: the time stamp information of the second sensing data is 00:00:00 at the minimum and 02:00:00 at the maximum, and the preset time interval may be determined to be 2 minutes assuming that the number of the preset second sensing data sets is 60.
And according to the timestamp information of the second sensing data, carrying out one-time segmentation on the second sensing data at preset time intervals, wherein at least one second transmission data obtained by each segmentation forms a second sensing data set. For example: if the preset time interval is 2 minutes, dividing the timestamp information of the second sensing data into: 00:00: 00-00: 02:00, 00:02: 01-00: 04:00, … …, 01:58: 01-02: 00:00, namely, second sensing data with time stamp information in 00:00: 00-00: 02:00 form a second sensing data set, and by analogy, a plurality of second sensing data sets can be obtained.
For any second sensing data set, an intermediate time in the second sensing data set may be determined, and the intermediate time may be an intermediate value of the start time and the end time of the second sensing data set, for example: the corresponding start time and end time of the second sensing data set are: 00:00:00 to 00:02:00, and the intermediate time is 00:01: 00. The second sensing data corresponding to the intermediate time can be determined, the physical position information corresponding to the second sensing data is used as the position information of the data acquisition point corresponding to the second sensing data set, and the physical position information corresponding to other second sensing data in the second sensing data is updated to the position information of the data acquisition point, so that a plurality of second sensing data acquired at the data acquisition point are obtained.
And in this way, after the physical position information of each second sensing data set is updated, a plurality of second sensing data sets acquired at a plurality of data acquisition points are obtained, and then a positioning model can be established according to the plurality of second sensing data sets.
In a possible implementation manner, the 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 second sensing data with physical position information according to a preset position interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to intermediate position information, wherein the intermediate position information is an intermediate value between the physical position information of the first second sensing data in the second sensing data set and the physical position information of the last second sensing data.
For example, the preset position interval may be a preset value, or may also be determined according to the physical position information and the number of the preset second sensing data sets, for example: the farthest distance between all the second sensing data sets collected is 120m, and assuming that the number of the preset second sensing data sets is 60, the preset time interval may be determined to be 2 m.
And according to the physical position information of the second sensing data, carrying out one-time segmentation on the second sensing data at preset position intervals, wherein at least one second transmission data obtained by each segmentation forms a second sensing data set. For example: and if the preset position interval is 2m, segmenting the second sensing data at intervals of 2m, forming a second sensing data set by a plurality of second sensing data obtained by each segmentation, and repeating the steps to obtain a plurality of second sensing data sets.
For any second sensing data set, intermediate position information in the second sensing data set may be determined, and the intermediate position information may be intermediate values of physical position information corresponding to first second sensing data and physical position information corresponding to last second sensing data of the second sensing data set, for example: the physical position information of the first second sensing data corresponding to the second sensing data set is (x1, y1), and the physical position information of the last second sensing data is (x2, y2), so the intermediate position information is ((x1+ x2)/2, (y1+ y 2)/2). The intermediate position information may be used as position information of a data acquisition point corresponding to the second sensing data set, and physical position information corresponding to a plurality of second sensing data in the second sensing data may be updated to position information of the data acquisition point, so as to obtain a plurality of second sensing data acquired at the data acquisition point.
And in this way, after the physical position information of each second sensing data set is updated, a plurality of second sensing data sets acquired at a plurality of data acquisition points are obtained, and then a positioning model can be established according to the plurality of second sensing data sets.
Therefore, the second sensing data set used for training the positioning model can be obtained without presetting data acquisition points and manually marking the physical positions of the sensing data, the data acquisition efficiency can be improved, and the training precision of the positioning model can be improved.
In one possible implementation, the method may further include:
and training a sensing positioning model through the second sensing data set to obtain the sensing positioning model, wherein the sensing positioning model is used for positioning according to the sensing data acquired by the second sensing equipment.
For example, for any second sensing device, after a plurality of second sensing data sets corresponding to the second sensing device are obtained, each second sensing data set may be used as sample data, physical location information corresponding to second sensing data in each second sensing data set is used as tagging information of the sample data, and a sensing positioning model corresponding to the second sensing device is obtained through training of the second sensing data set. And then in the positioning process, a corresponding positioning result can be obtained through the sensing positioning model according to second sensing data acquired by the second sensing equipment.
Illustratively, after the positioning model is established according to the first sensing data and the corresponding sensing positioning model is established according to the second sensing data, the subsequent fusion positioning can be performed, that is, the first positioning result is obtained according to the sensing data and the positioning model acquired by the first sensing equipment, the second positioning result is obtained according to the sensing data and the sensing positioning model acquired by the second sensing equipment, and the first positioning result and the second positioning result are fused to obtain the final positioning result.
Because the sensing data of the sensing positioning models used for training the second sensing devices are acquired simultaneously and the physical position information is aligned according to the acquisition time, the accuracy of the fusion positioning result can be improved and the robustness of the positioning service can be improved when the fusion positioning is carried out on the sensing positioning models obtained through training.
It is understood that the above-mentioned method embodiments of the present disclosure can be combined with each other to form a combined embodiment without departing from the logic of the principle, which is limited by the space, and the detailed description of the present disclosure is omitted. Those skilled in the art will appreciate that in the above methods of the specific embodiments, the specific order of execution of the steps should be determined by their function and possibly their inherent logic.
In addition, the present disclosure also provides a data processing apparatus, an electronic device, a computer-readable storage medium, and a program, which can be used to implement any data processing method provided by the present disclosure, and the corresponding technical solutions and descriptions and corresponding descriptions in the method section are not repeated.
Fig. 4 shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure, which, as shown in fig. 4, includes:
an obtaining module 41, configured to obtain a plurality of pieces of data information collected for a target area, where the data information includes first sensing data and second sensing data;
a model establishing module 42, configured to establish a positioning model corresponding to the target area according to the first sensing data;
a first processing module 43, configured to obtain physical location information of the first sensing data according to the positioning model;
the second processing module 44 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, a plurality of data information for the target area may be acquired, where the data information may include the first sensing data and the second sensing data, and a positioning model corresponding to the target area may 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 further, according to the physical position information of the first sensing data, the physical position information of the second sensing data can be obtained. According to the data processing device provided by the embodiment of the disclosure, the physical position information of the second sensing data acquired at the same time can be determined through the physical position information of the first sensing data, the physical position information of the data acquisition point and the sensing data marked manually does not need to be preset, the data acquisition efficiency can be improved, and the accuracy of the physical position information obtained through the positioning model is higher, so that the accuracy of each obtained sensing data can be improved.
In a possible implementation manner, the second processing module 44 may be further configured to:
and obtaining the physical position information of second sensing data acquired at the same time with the first sensing data according to the physical position information of the first sensing data.
In a possible implementation manner, the first sensing data and the second sensing data have timestamp information, and the second processing module 44 is further configured to:
determining first sensing data and second sensing data having the same timestamp information;
and taking the physical position information of the first sensing data as the physical position information of second sensing data with the same time stamp information as the first sensing data.
In one 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 one possible implementation, the apparatus may further include:
and the data segmentation module is used for carrying out data segmentation processing on the second sensing data with the physical position information to obtain at least one second sensing data set.
In a possible implementation manner, the data slicing module may be further configured to:
segmenting second sensing data with physical position information according to a preset time interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to the physical position information of the second sensing data corresponding to the intermediate time, wherein the intermediate time is the intermediate value of the starting time and the ending time of the second sensing data set.
In a possible implementation manner, the data slicing module may be further configured to:
segmenting second sensing data with physical position information according to a preset position interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to intermediate position information, wherein the intermediate position information is an intermediate value between the physical position information of the first second sensing data in the second sensing data set and the physical position information of the last second sensing data.
In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.
Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-mentioned method. 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 for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.
The embodiments of the present disclosure also provide a computer program product, which includes computer readable code, and when the computer readable code runs on a device, a processor in the device executes instructions for implementing the data processing method provided in any one of the above embodiments.
The embodiments of the present disclosure also provide another computer program product for storing computer readable instructions, which when executed cause a computer to perform the operations of the data processing method provided in any of the above embodiments.
The electronic device may be provided as a terminal, server, or other form of device.
Fig. 5 illustrates a block diagram of an electronic device 800 in accordance with an embodiment of the disclosure. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.
Referring to fig. 5, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices 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 disks.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a 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 an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 800 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the 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 peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the electronic device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The 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.
The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as a wireless network (WiFi), a second generation mobile communication technology (2G) or a third generation mobile communication technology (3G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. 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, the 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 Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium, such as the memory 804, is also provided that includes computer program instructions executable by the processor 820 of the electronic device 800 to perform the above-described methods.
Fig. 6 illustrates a block diagram of an electronic device 1900 in accordance with an embodiment of the disclosure. For example, the electronic device 1900 may be provided as a server. Referring to fig. 6, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The electronic device 1900 may also include a power component 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 may operate based on an operating system, such as the Microsoft Server operating system (Windows Server), stored in the memory 1932TM) Apple Inc. of the present application based on the graphic user interface operating System (Mac OS X)TM) Multi-user, multi-process computer operating system (Unix)TM) Free and open native code Unix-like operating System (Linux)TM) Open native code Unix-like operating System (FreeBSD)TM) Or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the electronic device 1900 to perform the above-described methods.
The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via 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. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming 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. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various 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, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
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 executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown 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 will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The computer program product may be embodied in hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many 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 is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (10)

1. A data processing method, comprising:
acquiring a plurality of pieces of data information acquired aiming at a target area, wherein the data information comprises first sensing data and second sensing data;
establishing a positioning model corresponding to the target area according to the first sensing data;
obtaining physical position information of the first sensing data according to the positioning model;
and obtaining the physical position information of the second sensing data according to the physical position information of the first sensing data.
2. The method of claim 1, wherein obtaining the physical location information of the second sensing data according to the physical location information of the first sensing data comprises:
and obtaining the physical position information of second sensing data acquired at the same time with the first sensing data according to the physical position information of the first sensing data.
3. The method of claim 2, wherein the first sensing data and the second sensing data have timestamp information, and the obtaining physical location information of the second sensing data collected at the same time as the first sensing data according to the physical location information of the first sensing data comprises:
determining first sensing data and second sensing data having the same timestamp information;
and taking the physical position information of the first sensing data as the physical position information of second sensing data with the same time stamp information as the first sensing data.
4. The method of claim 3, wherein the time stamp information of the first sensory data and the time stamp information of the second sensory data are determined by a same clock system.
5. The method according to any one of claims 1 to 4, further comprising:
and carrying out data segmentation processing on the second sensing data with the physical position information to obtain at least one second sensing data set.
6. The method according to claim 5, wherein the performing a data slicing process on the second sensing data with physical location information to obtain at least one second sensing data set comprises:
segmenting second sensing data with physical position information according to a preset time interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to the physical position information of the second sensing data corresponding to the intermediate time, wherein the intermediate time is the intermediate value of the starting time and the ending time of the second sensing data set.
7. The method according to claim 5, wherein the performing a data slicing process on the second sensing data with physical location information to obtain at least one second sensing data set comprises:
segmenting second sensing data with physical position information according to a preset position interval to obtain at least one second sensing data set;
and for any second sensing data set, updating the physical position information of the second sensing data in the second sensing data set according to intermediate position information, wherein the intermediate position information is an intermediate value between the physical position information of the first second sensing data in the second sensing data set and the physical position information of the last second sensing data.
8. A data processing apparatus, comprising:
the acquisition module is used for acquiring a plurality of data information acquired aiming at a target area, wherein the data information comprises first sensing data and second sensing data;
the model establishing module is used for establishing a positioning model corresponding to the target area according to the first sensing data;
the first processing module is used for obtaining physical position information of the first sensing data according to the positioning model;
and the second processing module is used for obtaining the physical position information of the second sensing data according to the physical position information of the first sensing data.
9. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the memory-stored instructions to perform the method of any of claims 1 to 7.
10. A computer readable storage medium having computer program instructions stored thereon, which when executed by a processor implement the method of any one of claims 1 to 7.
CN202011355417.1A 2020-11-26 2020-11-26 Data processing method and device, electronic equipment and storage medium Pending CN112461245A (en)

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