WO2022068626A1

WO2022068626A1 - Track correction method and system

Info

Publication number: WO2022068626A1
Application number: PCT/CN2021/119278
Authority: WO
Inventors: 张康; 程国红; 郭永峰; 王晓力
Original assignee: 华为技术有限公司
Priority date: 2020-09-30
Filing date: 2021-09-18
Publication date: 2022-04-07
Also published as: CN114363821B; CN114363821A

Abstract

Provided in the embodiments of the present application are a track correction method and system. The method comprises: a first electronic device sends to a cloud server a plurality of obtained motion tracks; and the cloud server can obtain a third motion track on the basis of the received plurality of motion tracks sent by the first electronic device. The first electronic device can correct, on the basis of the third motion track obtained from the cloud server, the deviation of a motion track uploaded by a second electronic device, and display the corrected motion track, thereby providing a way to correct, on the basis of a motion track, the deviation of another motion track, so as to weaken the dependence on road network data in a deviation correction process. Even in the scenario in which there is no road network data in the first electronic device, a motion track that has undergone deviation correction and is displayed by the first electronic device can still have high similarity with an actual motion track, thus improving the accuracy of the motion track that has undergone deviation correction and the usage experience of a user.

Description

Track deviation correction method and system

This application claims the priority of the Chinese patent application with the application number 202011063430.X and the application name "Track Correction Method and System" submitted to the State Intellectual Property Office of China on September 30, 2020, the entire contents of which are incorporated herein by reference Applying.

technical field

The embodiments of the present application relate to the field of terminals, and in particular, to a trajectory deviation correction method and system.

Background technique

At present, with the development of communication technology, the functions of smart devices (such as smart bracelets, smart watches, etc.) are becoming more and more powerful, and their application scenarios are becoming more and more extensive. For example, a user can run with a smart watch and record the user's movement track through the smart watch. Then, the user can connect the smart watch to the mobile phone and upload the movement track recorded by the smart watch to the mobile phone to display the user's movement through the mobile phone. trajectory.

However, due to the hardware limitations of smart devices such as smart watches, there is a large deviation between the motion trajectory obtained by the smart watch and the user's actual motion trajectory. Therefore, the user's motion trajectory displayed by the mobile phone may deviate more from the actual motion trajectory. The problem.

SUMMARY OF THE INVENTION

In order to solve the above technical problems, the present application proposes a trajectory correction method and system. In this method, the motion trajectory uploaded by the second electronic device can be corrected by the first electronic device based on the motion trajectory obtained from the cloud server, so as to correct the deviation of the non-standard motion trajectory with the standard motion trajectory, In a way that the motion trajectory can be corrected without relying on the road network data, the accuracy of the motion trajectory displayed by the first electronic device is effectively improved.

In a first aspect, a trajectory correction system is provided. The system includes: a cloud server, a first electronic device and a second electronic device, the first electronic device is connected to the second electronic device through Bluetooth, and the first electronic device performs data interaction with the cloud server through a cellular network; the first electronic device uses To: obtain the first motion track and the second motion track within the first area, and send the first motion track and the second motion track to the cloud server; the cloud server is used for: according to the received first motion track and the second motion track a motion trajectory, to obtain a third motion trajectory; a first electronic device, for: acquiring a third motion trajectory from a cloud server; a second electronic device, for: acquiring a fourth motion trajectory within the first area; The device sends a fourth motion trajectory; the first electronic device is further configured to: in response to the received fourth motion trajectory, correct the fourth motion trajectory based on the third motion trajectory, and display the corrected fourth motion trajectory. In this way, the first electronic device can correct the motion trajectory uploaded by the second electronic device based on the motion trajectory obtained from the cloud server, so as to improve the similarity between the displayed motion trajectory and the actual motion trajectory.

Exemplarily, the first electronic device may also send a third motion trajectory, a fourth motion trajectory, etc. to the cloud server, and the first to fourth motion trajectories are all acquired by the first electronic device within the first area, and the cloud server Based on more motion trajectories sent by the first electronic device, a motion trajectory with a higher similarity to the actual motion trajectory can be obtained. The first electronic device can correct the motion trajectory of the second electronic device based on the motion trajectory trained by the cloud server, so that the similarity between the motion trajectory displayed by the first electronic device and the actual motion trajectory is further improved.

Exemplarily, the manner in which the cloud server obtains the third motion trajectory includes: performing similarity matching between the first motion trajectory and a plurality of stored motion trajectories; if there is a successful similarity matching with the first motion trajectory , obtain the third motion trajectory according to the motion trajectory successfully matched by the similarity, the first motion trajectory and the second motion trajectory; if the multiple motion trajectories match the first motion trajectory The trajectory similarity matching fails, and the third motion trajectory is acquired according to the first motion trajectory and the second motion trajectory.

Exemplarily, there is a projection point corresponding to at least one trajectory point on the first movement trajectory on the motion trajectory for which the similarity is successfully matched, wherein the number of the projection points is greater than a first threshold, and the projection point The distance from the corresponding trajectory point on the first motion trajectory is smaller than the second threshold, and the direction difference between the direction of the projection point and the corresponding trajectory point on the first motion trajectory is smaller than the third threshold.

Exemplarily, there is a projection point corresponding to at least one trajectory point on the fourth movement trajectory on the third movement trajectory, wherein the number of the projection points is greater than the first threshold, and the projection point is the same as the projection point. The distance between the corresponding trajectory points on the fourth motion trajectory is smaller than the second threshold, and the direction difference between the direction of the projection point and the corresponding trajectory point on the fourth motion trajectory is smaller than the third threshold.

Exemplarily, if there is a jump track point on the fourth motion track, the fourth motion track after the deviation correction includes the jump track point; the fourth motion track satisfies any of the following conditions: The trajectory point is the jump trajectory point: the direction difference with the previous trajectory point or the next trajectory point is greater than the fourth threshold; the speed difference with the previous trajectory point or the next trajectory point is greater than the fifth threshold; The distance difference from the previous trajectory point or the next trajectory point is greater than the sixth threshold.

According to the first aspect, the system further includes a third electronic device, and the third electronic device performs data interaction with the cloud server through the cellular network; the third electronic device is used for: acquiring the fifth motion trajectory within the first area; the cloud server, is also used for: receiving the fifth motion trajectory; obtaining the sixth motion trajectory according to the fifth motion trajectory and the third motion trajectory; the first electronic device is also used for: acquiring the sixth motion trajectory from the cloud server; the second electronic device, used for: acquiring the seventh motion trajectory within the range of the first area; sending the seventh motion trajectory to the first electronic device; the first electronic device is further used for: responding to the received seventh motion trajectory, based on the sixth motion trajectory , rectify the seventh motion track, and display the seventh motion track after the rectification. In this way, the cloud server can also be based on one or more other electronic devices, such as a third electronic device, and of course, it can also be the motion trajectory within the first area sent by the fourth electronic device, the fifth electronic device, etc. The motion trajectory is trained to obtain a more standard motion trajectory, so that the first electronic device can correct the motion trajectory of the second electronic device based on the seventh motion trajectory obtained after further training, thereby improving the accuracy of the displayed motion trajectory. sex.

According to the first aspect, or any implementation manner of the above first aspect, the system further includes a third electronic device, the third electronic device performs data interaction with the cloud server through the cellular network; the third electronic device is used to obtain the second area The eighth motion track and the ninth motion track within the range, the first area range is different from the second area range; the cloud server is also used for: receiving the eighth motion track and the ninth motion track; according to the eighth motion track and the ninth motion track The motion track is used to obtain the tenth motion track; the first electronic device is further used for: obtaining the tenth motion track from the cloud server; the first electronic device is also used for: combining the fourth motion track with the third motion track and the tenth motion track The trajectories are respectively matched for similarity, and it is determined that the similarity between the fourth motion trajectory and the third motion trajectory is successfully matched; based on the third motion trajectory whose similarity is successfully matched, the deviation of the fourth motion trajectory is corrected, and the corrected fourth motion trajectory is displayed. . In this way, the cloud server can obtain one or more standard motion trajectories corresponding to the region based on the motion trajectories in the different regions (that is, the third motion track corresponding to the first region and the tenth motion corresponding to the second region). motion trajectory), the first electronic device can obtain one or more standard motion trajectories (such as the third motion trajectory and the tenth motion trajectory) from the cloud server, and then the first electronic device can upload the motion trajectory uploaded by the second electronic device Perform similarity matching with one or more obtained standard motion trajectories, and correct the motion trajectory uploaded by the second electronic device based on the successfully matched standard trajectory (for example, the third motion trajectory), so as to improve the displayed motion accuracy of the trajectory.

According to the first aspect, or any implementation manner of the above first aspect, the similarity between the first motion trajectory and the second motion trajectory is greater than or equal to a similarity threshold. In this way, the cloud server can perform training based on multiple motion trajectories within the same area and whose similarity is greater than a threshold, so as to obtain a standard motion trajectory. Exemplarily, the similarity between multiple motion trajectories in the same area uploaded by the same electronic device, or the similarity between multiple motion trajectories in the same area uploaded by different electronic devices may be greater than or equal to the similarity. Threshold, the cloud server can obtain standard motion trajectories based on multiple motion trajectories within the same area uploaded by the same electronic device or different electronic devices. Exemplarily, the similarity between multiple motion trajectories within the same area uploaded by the same electronic device or different electronic devices may be less than the similarity threshold, and the cloud server may perform similarity matching on the multiple motion trajectories. , to obtain two or more motion trajectories with a similarity greater than or equal to the similarity threshold, and train the two or more motion trajectories to obtain a standard motion trajectory, that is, the same area The range can correspond to one or more marked motion trajectories.

According to the first aspect, or any implementation manner of the above first aspect, the first electronic device is configured to: receive an instruction from a user, and acquire a third motion trajectory from a cloud server in response to the instruction from the user. In this way, the first electronic device can actively request the cloud server for the third motion trajectory based on the user's instruction, and obtain the third motion trajectory. Exemplarily, the user's instruction may also instruct the first electronic device to obtain a specified area from the cloud server, such as a motion trajectory within the second area, and the first electronic device may request the cloud server for the second area based on the user's instruction. trajectory within.

According to the first aspect, or any implementation manner of the above first aspect, the cloud server is configured to: send indication information to the first electronic device, for indicating that the first electronic device can download the third motion trajectory from the cloud server. In this way, after acquiring the third motion trajectory, the cloud server can notify the first electronic device that there is currently a downloadable third motion trajectory by sending indication information. Exemplarily, the cloud server may record an area range corresponding to the first electronic device, and accordingly, after the cloud server generates a motion trajectory corresponding to the area range, the cloud server may send indication information to the first electronic device. Exemplarily, the first electronic device may display the undownloaded motion track that exists in the cloud server within the specified area on the application interface of the sports health application, or pull down the notification bar, or the notification bar when the screen is locked. The first electronic device may download the motion trajectory within the specified area from the cloud server in response to the received user's instruction.

According to the first aspect, or any implementation manner of the above first aspect, the first electronic device is a mobile phone, and the second electronic device is a smart watch. In this way, one or more motion trajectories are acquired through the first electronic device (that is, the mobile phone) with relatively strong positioning capability, and the cloud server trains one or more motion trajectories sent by the mobile phone, so as to obtain a high similarity with the actual motion trajectories. Standard motion trajectory. The mobile phone can correct the motion trajectory uploaded by the smart watch with weak positioning ability based on the motion trajectory trained by the cloud server, so as to improve the similarity between the corrected motion trajectory and the actual motion trajectory, so as to effectively improve the user experience.

According to the first aspect, or any implementation manner of the above first aspect, the first electronic device and the second electronic device are respectively installed with a sports health application. In this way, the first electronic device and the second electronic device can be paired through the sports health application and perform data interaction, for example, the second electronic device can send the acquired motion trajectory to the first electronic device through the sports health application.

According to the first aspect, or any implementation manner of the above first aspect, the first electronic device is configured to: display the fourth motion trajectory after deviation correction on the application interface of the sports health application. Exemplarily, the sports health application may also call the road network data of the map application to display the fourth motion trajectory after deviation correction at the corresponding position on the map.

According to the first aspect, or any implementation manner of the above first aspect, the first electronic device and the second electronic device have the same user account. In this way, the user can log in to the first electronic device and the second electronic device through the user account, and the first electronic device and the second electronic device can perform data interaction in the scenario of having the same user account.

In a second aspect, a trajectory correction method is provided. The method is applied to a communication system, and the system includes: a cloud server, a first electronic device and a second electronic device, the first electronic device is connected to the second electronic device through Bluetooth, and the first electronic device exchanges data with the cloud server through a cellular network; The method includes: the first electronic device acquires the first motion track and the second motion track within the first area, and sends the first motion track and the second motion track to the cloud server; the cloud server obtains the first motion track and the second motion track according to the received The second motion track is to obtain the third motion track; the first electronic device obtains the third motion track from the cloud server; the second electronic device obtains the fourth motion track within the first area, and sends the fourth motion track to the first electronic device ; In response to the received fourth motion trajectory, the first electronic device corrects the fourth motion trajectory based on the third motion trajectory, and displays the corrected fourth motion trajectory.

According to the second aspect, the system further includes a third electronic device, and the third electronic device performs data interaction with the cloud server through the cellular network; the method further includes: the third electronic device acquires a fifth motion trajectory within the first area; the cloud server receives the fifth motion track, and obtain the sixth motion track according to the fifth motion track and the third motion track; the first electronic device obtains the sixth motion track from the cloud server; the second electronic device obtains the seventh motion within the first area track, and send the seventh motion track to the first electronic device; the first electronic device, in response to the received seventh motion track, corrects the seventh motion track based on the sixth motion track, and displays the corrected seventh motion track trajectory.

According to the second aspect, or any implementation manner of the above second aspect, the system further includes a third electronic device, and the third electronic device performs data interaction with the cloud server through a cellular network; the method further includes: the third electronic device obtains the second The eighth motion track and the ninth motion track within the area range, the first area range is different from the second area range; the cloud server receives the eighth motion track and the ninth motion track, and according to the eighth motion track and the ninth motion track, obtaining the tenth motion trajectory; the first electronic device obtains the tenth motion trajectory from the cloud server; the first electronic device performs similarity matching on the fourth motion trajectory with the third motion trajectory and the tenth motion trajectory respectively, and determines the fourth motion trajectory The similarity with the third motion trajectory is successfully matched; and, based on the third motion trajectory, the fourth motion trajectory is rectified, and the rectified fourth motion trajectory is displayed.

According to the second aspect, or any implementation manner of the above second aspect, the similarity between the first motion trajectory and the second motion trajectory is greater than or equal to a similarity threshold.

According to the second aspect, or any implementation manner of the above second aspect, the first electronic device receives the user's instruction, and in response to the user's instruction, acquires the third motion trajectory from the cloud server.

According to the second aspect, or any implementation manner of the above second aspect, the cloud server sends indication information to the first electronic device, which is used to indicate that the first electronic device can download the third motion trajectory from the cloud server.

According to the second aspect, or any implementation manner of the above second aspect, the first electronic device is a mobile phone, and the second electronic device is a smart watch.

According to the second aspect, or any implementation manner of the above second aspect, the first electronic device and the second electronic device are respectively installed with a sports health application.

According to the second aspect, or any implementation manner of the above second aspect, the first electronic device displays the fourth motion trajectory after deviation correction on the application interface of the sports health application.

According to the second aspect, or any implementation manner of the above second aspect, the first electronic device and the second electronic device have the same user account.

The second aspect and any implementation manner of the second aspect correspond to the first aspect and any implementation manner of the first aspect, respectively. For the technical effects corresponding to the second aspect and any implementation manner of the second aspect, reference may be made to the technical effects corresponding to the first aspect and any implementation manner of the first aspect, which will not be repeated here.

In a third aspect, a computer-readable storage medium is provided. The medium includes a computer program that, when the computer program runs on the electronic device or the cloud server, causes the electronic device or the cloud server to execute the second aspect and the trajectory correction method in any one of the second aspect. Exemplarily, the electronic device may be the first electronic device or the second electronic device.

The third aspect and any implementation manner of the third aspect correspond to the first aspect and any implementation manner of the first aspect, respectively. For the technical effects corresponding to the third aspect and any implementation manner of the third aspect, reference may be made to the technical effects corresponding to the first aspect and any implementation manner of the first aspect, which will not be repeated here.

In a fourth aspect, an embodiment of the present application provides a computer program, where the computer program includes instructions for executing the method in the second aspect or any possible implementation manner of the second aspect.

The fourth aspect and any implementation manner of the fourth aspect correspond to the first aspect and any implementation manner of the first aspect, respectively. For the technical effects corresponding to the fourth aspect and any implementation manner of the fourth aspect, reference may be made to the technical effects corresponding to the first aspect and any implementation manner of the first aspect, which will not be repeated here.

In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processing circuit and a transceiver pin. Wherein, the transceiver pin and the processing circuit communicate with each other through an internal connection path, and the processing circuit executes the method in the second aspect or any possible implementation manner of the second aspect to control the receiving pin to receive a signal to Control the send pin to send the signal. Exemplarily, the chip may be a chip of a cloud server or a chip of an electronic device, and the electronic device may be a first electronic device or a second electronic device.

The fifth aspect and any implementation manner of the fifth aspect correspond to the first aspect and any implementation manner of the first aspect, respectively. For the technical effects corresponding to the fifth aspect and any implementation manner of the fifth aspect, reference may be made to the technical effects corresponding to the first aspect and any implementation manner of the first aspect, which will not be repeated here.

Description of drawings

FIG. 1 is a schematic diagram of an exemplary illustrated communication system;

2 is a schematic structural diagram of an exemplary mobile phone;

3 is a schematic diagram of the software structure of an exemplary mobile phone;

4 is a schematic diagram of the software structure of an exemplary smart watch;

5 is a schematic diagram of an exemplary application scenario;

Fig. 6 is a schematic diagram of a trajectory correction flow diagram exemplarily shown;

Fig. 7a is a schematic diagram of the motion trajectory before deviation correction shown in an exemplary manner;

Fig. 7b is a schematic diagram of the motion trajectory after the deviation correction is exemplarily shown;

8 is a schematic flowchart of a trajectory correction method provided by an embodiment of the present application;

FIG. 9 is a schematic flowchart of the standard path training exemplarily shown;

FIG. 10 is a schematic flowchart of an exemplary standard path download;

FIG. 11 is a schematic flowchart of an exemplary trajectory correction;

FIG. 12 is a schematic diagram of application pairing exemplarily shown;

FIG. 13 is a schematic flowchart of standard path training exemplarily shown;

FIG. 14 is a schematic flowchart of an exemplary similarity matching;

FIG. 15 is a schematic flowchart of standard path training exemplarily shown;

FIG. 16 is a schematic flowchart of an exemplary trajectory correction;

FIG. 17 is a schematic flowchart of the standard path training exemplarily shown;

FIG. 18 is a schematic flowchart of standard path training exemplarily shown;

FIG. 19 is a schematic flowchart of an exemplary similarity matching;

20 is a schematic flowchart of a trajectory correction method provided by an embodiment of the present application;

21 is a schematic flowchart of a trajectory correction method provided by an embodiment of the present application;

Figure 22 is a schematic diagram of an exemplary application scenario;

Figures 23a-23b are schematic diagrams of motion trajectories exemplarily shown;

FIG. 24 is a schematic diagram of an exemplary display interface;

FIG. 25 is a schematic diagram of an exemplarily shown display interface.

26 is a schematic flowchart of a trajectory correction method provided by an embodiment of the present application;

FIG. 27 is a schematic structural diagram of an apparatus provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

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.

The terms "first" and "second" in the description and claims of the embodiments of the present application are used to distinguish different objects, rather than to describe a specific order of the objects. For example, the first target object, the second target object, etc. are used to distinguish different target objects, rather than to describe a specific order of the target objects.

In the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or illustrations. Any embodiments or designs described in the embodiments of the present application as "exemplary" or "such as" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present the related concepts in a specific manner.

In the description of the embodiments of the present application, unless otherwise specified, the meaning of "plurality" refers to two or more. For example, multiple processing units refers to two or more processing units; multiple systems refers to two or more systems.

Before describing the technical solutions of the embodiments of the present application, the communication system of the embodiments of the present application is first described with reference to the accompanying drawings. Referring to FIG. 1 , it is a schematic diagram of a communication system according to an embodiment of the present application. The communication system includes the cloud, mobile phones and smart watches. As shown in Figure 1, the smart watch can communicate with the mobile phone, and the mobile phone can communicate with the cloud. Exemplarily, data can be exchanged between the smart watch and the mobile phone through a Bluetooth network, and data can be exchanged between the mobile phone and the cloud through a cellular network. It should be noted that, in the description of the embodiments of the present application, the cloud includes one or more network devices for providing services for terminal devices. The number of mobile phones and smart watches is only a schematic example. In practical application scenarios, the number of both mobile phones and smart watches may be one or more.

In the description of the embodiments of the present application, smart watches and mobile phones are used as examples for illustration. In other embodiments, the present application is also applicable to large screens, laptop computers, desktop The connection scenario between electronic devices such as smart phones, etc. and smart wearable devices (such as smart bracelets, smart watches, smart glasses, smart rings, etc.).

FIG. 2 is a schematic structural diagram of a mobile phone according to an embodiment of the application. Although FIG. 2 takes the mobile phone in FIG. 1 as an example to illustrate the structure of the electronic device, those skilled in the art will understand that the structure of the mobile phone in FIG. 2 is also applicable to the smart watch in FIG. 1 . As shown in FIG. 2 , the mobile phone 100 may include a processor 110 , an external memory interface 120 , an internal memory 121 , a USB interface 130 , a charging management module 140 , a power management module 141 , a battery 142 , an antenna 1 , an antenna 2 , and a mobile communication module 150 , the wireless communication module 160, the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone jack 170D, the sensor module 180, the buttons 190, the motor 191, the indicator 192, the camera 193, the display screen 194, and the subscriber identification module (subscriber identification module, SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, and ambient light. Sensor 180L, bone conduction sensor 180M, etc.

It can be understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the mobile phone 100 . In other embodiments of the present application, the mobile phone 100 may include more or less components than shown, or some components may be combined, or some components may be separated, or different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), controller, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural-network processing unit (neural-network processing unit, NPU), etc. Wherein, different processing units may be independent devices, or may be integrated in one or more processors.

The controller can generate an operation control signal according to the instruction operation code and timing signal, and complete the control of fetching and executing instructions.

A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in processor 110 is cache memory. This memory may hold instructions or data that have just been used or recycled by the processor 110 . If the processor 110 needs to use the instruction or data again, it can be called directly from the memory. Repeated accesses are avoided and the latency of the processor 110 is reduced, thereby increasing the efficiency of the system.

The USB interface 130 is an interface that conforms to the USB standard specification, specifically a Mini USB interface, a Micro USB interface, a USB Type C interface, etc., and can support USB1.0, USB2.0, USB3.0 and USB4.0 or higher standard USB Specifications, including various USB specifications. Exemplarily, the USB interface 130 may include one or more USB interfaces.

It can be understood that the interface connection relationship between the modules illustrated in the embodiments of the present application is only a schematic illustration, and does not constitute a structural limitation of the mobile phone 100 . In other embodiments of the present application, the mobile phone 100 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.

The charging management module 140 is used to receive charging input from the charger. The power management module 141 is used for connecting the battery 142 , the charging management module 140 and the processor 110 . The wireless communication function of the mobile phone 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modulation and demodulation processor, the baseband processor, and the like.

Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in handset 100 may be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, the antenna 1 can be multiplexed as a diversity antenna of the wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 150 can provide wireless communication solutions including 2G/3G/4G/5G etc. applied on the mobile phone 100 . The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA) and the like. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, filter and amplify the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and then turn it into an electromagnetic wave for radiation through the antenna 1 . In some embodiments, at least part of the functional modules of the mobile communication module 150 may be provided in the processor 110 . In some embodiments, at least part of the functional modules of the mobile communication module 150 may be provided in the same device as at least part of the modules of the processor 110 .

The wireless communication module 160 can provide applications on the mobile phone 100 including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) network), bluetooth (BT), global navigation satellite system (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), near field communication technology (near field communication, NFC), infrared technology (infrared, IR) and other wireless communication solutions. The wireless communication module 160 may be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2 , frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110 . The wireless communication module 160 can also receive the signal to be sent from the processor 110 , perform frequency modulation on it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2 .

In some embodiments, the antenna 1 of the mobile phone 100 is coupled with the mobile communication module 150, and the antenna 2 is coupled with the wireless communication module 160, so that the mobile phone 100 can communicate with the network and other devices through wireless communication technology. The wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), broadband Code Division Multiple Access (WCDMA), Time Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN, NFC , FM, and/or IR technology, etc. The GNSS may include global positioning system (global positioning system, GPS), global navigation satellite system (global navigation satellite system, GLONASS), Beidou navigation satellite system (beidou navigation satellite system, BDS), quasi-zenith satellite system (quasi -zenith satellite system, QZSS) and/or satellite based augmentation systems (SBAS).

The mobile phone 100 can realize the shooting function through the ISP, the camera 193, the video codec, the GPU, the display screen 194 and the application processor.

The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the mobile phone 100 . The external memory card communicates with the processor 110 through the external memory interface 120 to realize the data storage function. For example to save files like music, video etc in external memory card.

The mobile phone 100 can implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, and an application processor. Such as music playback, recording, etc.

FIG. 3 is a block diagram of a software structure of a mobile phone 100 according to an embodiment of the present application. The layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Layers communicate with each other through software interfaces. In some embodiments, the Android system is divided into five layers, which are, from top to bottom, an application layer, a system framework layer, a system library and runtime layer, and a kernel layer.

The application layer can include applications such as camera, gallery, calendar, sports health, WLAN, music, video, etc. It should be noted that, the applications included in the application layer shown in FIG. 3 are only illustrative, and are not limited in this application. It can be understood that the applications included in the application layer do not constitute a specific limitation on the mobile phone 100 . In other embodiments of the present application, compared with the applications included in the application layer shown in FIG. 3 , the mobile phone 100 may include more or less applications, and the mobile phone 100 may also include completely different applications.

The system framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer, including various components and services to support developers' Android development. The system framework layer includes some predefined functions. As shown in FIG. 3, the system framework layer may include a view system, a window manager, a resource manager, a content provider, and the like. The view system includes visual controls, such as controls for displaying text, controls for displaying pictures, and so on. View systems can be used to build applications. A display interface can consist of one or more views. A window manager is used to manage window programs. The window manager can get the size of the display screen, determine whether there is a status bar, lock the screen, take screenshots, etc. The resource manager provides various resources for the application, such as localization strings, icons, pictures, layout files, video files and so on. Content providers are used to store and retrieve data and make these data accessible to applications. The data may include video, images, audio, and the like.

The system library and runtime layer includes the system library and the Android Runtime. A system library can include multiple functional modules. For example: browser kernel, 3D graphics library (eg: OpenGL ES), font library, etc. The browser kernel is responsible for interpreting the syntax of the web page (such as an application HTML and JavaScript under the standard general markup language) and rendering (displaying) the web page. The 3D graphics library is used to implement 3D graphics drawing, image rendering, compositing and layer processing, etc. The font library is used to implement the input of different fonts. The Android runtime includes core libraries and a virtual machine. The Android runtime is responsible for the scheduling and management of the Android system. The core library consists of two parts: one is the function functions that the java language needs to call, and the other is the core library of Android. The application layer and the application framework layer run in virtual machines. The virtual machine executes the java files of the application layer and the application framework layer as binary files. The virtual machine is used to perform functions such as object lifecycle management, stack management, thread management, safety and exception management, and garbage collection.

It can be understood that the components included in the system framework layer, system library and runtime layer shown in FIG. 3 do not constitute a specific limitation on the mobile phone 100 . In other embodiments of the present application, the mobile phone 100 may include more or less components than shown, or some components may be combined, or some components may be separated, or different component arrangements.

The kernel layer is the layer between hardware and software. The kernel layer contains at least display drivers, camera drivers, audio drivers, and sensor drivers.

FIG. 4 is a block diagram of a software structure of a smart watch 200 according to an embodiment of the present application. The layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Layers communicate with each other through software interfaces. In some embodiments, the software structure in the smart watch is divided into four layers, which are, from top to bottom, an application layer, a system framework layer, a hardware abstraction layer (Hardware Abstraction Layer, HAL), and a driver.

The application layer can include applications such as dials and segments. It should be noted that these applications can be understood as sub-functions in the sports health application, that is to say, the sports health application is embedded in the smart watch. , the sports health application is activated by default, and the user can select sub-applications in the sports health application, such as Duan Lian, etc., and select the corresponding mode. It should be noted that, the applications included in the application layer shown in FIG. 4 are only exemplary descriptions, which are not limited in this application. It can be understood that the applications included in the application layer do not constitute a specific limitation on the smart watch 200 . In other embodiments of the present application, compared with the applications included in the application layer shown in FIG. 4 , the smart watch 200 may include more or less applications, and the smart watch 200 may also include completely different applications.

The system framework layer provides application programming interface (API) and programming framework for the applications in the application layer. As shown in Figure 4, the system framework layer can include basic platform services, sports services, health services, short-distance services, Audio services, mobile phone collaboration services and other services. Exemplarily, basic platform services include device management, communication management, DFM, maintenance and testing camp, file system, secure storage, and upgrade services. Sports services include daily tracking, exercise, fitness, and wear detection. Health services include heart rate, stress, breathing, sleep, atrial fibrillation. Short-range services include Bluetooth, NFC payment, and positioning. Audio services include music playback and audio device management. Mobile phone collaboration services include call management and message management.

The HAL layer is used to isolate hardware differences, logically abstract the hardware, and form a unified interface, so that the system framework layer does not depend on specific hardware. This layer includes audio (Audio) HAL and sensor (Sensor) HAL.

It can be understood that the components included in the system framework layer and the HAL layer shown in FIG. 4 do not constitute a specific limitation on the smart watch 200 . In other embodiments of the present application, the smart watch 200 may include more or less components than shown, or combine some components, or separate some components, or arrange different components.

FIG. 5 is an exemplary schematic diagram of an application scenario. Referring to FIG. 5 , the user runs along the path A, and the actual motion trajectory of the user is the motion trajectory A shown in FIG. 5 . In an example, the user runs with a mobile phone, because the antenna efficiency of the mobile phone is relatively high (generally around -4.5dB ~ -5.5dB), and the number of satellite search channels is large (that is, more satellites can be found and connected, such as satellite search. The number of channels is 100 to 144), among which, the higher the antenna efficiency, the greater the gain of the GPS signal received by the mobile phone, and the more the number of satellites that can be searched and connected when the mobile phone is positioned, the more the mobile phone can obtain The more parameters that can be used for positioning, the more accurate, therefore, the motion trajectory obtained by the mobile phone (that is, the motion trajectory B in FIG. 5 ) is close to the actual motion trajectory A. In another example, the user only wears the smart watch for running (does not carry a mobile phone), because the antenna efficiency of the smart watch is low (generally about -11dB), and the number of search channels is small (for example, the number of search channels is 24-64). A), therefore, it may cause a large deviation between the motion track C obtained by the smart watch and the motion track A.

In order to solve the problem that the deviation between the motion trajectory acquired by the smart watch and the actual motion trajectory is relatively large, for example, the mobile phone can correct the deviation of the motion trajectory acquired by the smart watch. FIG. 6 is an exemplary schematic diagram of the trajectory correction process. Referring to FIG. 6 , it specifically includes:

In step 101, the mobile phone periodically or triggered downloads road network data from the cloud.

Exemplarily, the road network data is stored in the cloud, and the road network data is manually produced, and the specific production method is not described in this application.

Exemplarily, the mobile phone may periodically download road network data from the cloud, and optionally, the period may be 7 days, which is not limited in this application.

Exemplarily, the mobile phone may also download road network data from the cloud after receiving the user's instruction.

It should be noted that the road network data described in the embodiments of the present application refers to data including longitude and latitude. For example, the longitude and latitude data in the road network data obtained by the mobile phone can indicate parameters such as street width, location, length, etc. The map picture displayed by the software is usually the result of rendering each parameter of the road network data.

Step 102, the smart watch acquires motion track information.

Exemplarily, during the user's running process, the smart watch may collect motion track information according to a sampling period (for example, 1s). For example, the smart watch obtains the current motion information every 1s, and the motion information includes but is not limited to: position, direction, speed, confidence, and altitude (ie altitude). Save, it can be understood that the smart watch obtains the motion information of one track point every 1s. During the process from the user's start to the end of running, the track points obtained by the smart watch (for example, 1,000 track points are obtained) constitute the user. Therefore, the motion trajectory information described in the embodiments of the present application includes the motion information corresponding to each trajectory point that constitutes the motion trajectory, that is, the motion trajectory information includes but is not limited to the position of each trajectory point on the motion trajectory, Direction, speed, confidence and altitude.

Optionally, the smart watch can also obtain the user's health information, such as the user's pulse, body temperature, heart rate and other data.

Exemplarily, the position of the trajectory point described in the embodiments of the present application is the longitude and latitude information of the trajectory point.

Exemplarily, the direction of the trajectory point can be obtained by an electronic device (such as a mobile phone or a smart watch) based on the received GPS signal, or it can be based on the distance between the trajectory point and the previous trajectory point and/or the next trajectory point. obtained from the location. It should be noted that the direction of the trajectory point obtained through the position between the trajectory point and the previous trajectory point and/or the next trajectory point may have a certain deviation from the actual direction of the trajectory point, which can be understood as the trajectory The directional trend (or movement trend) corresponding to the point.

Exemplarily, the velocity of the trajectory point may be directly measured, or it may be calculated based on the displacement from the previous trajectory point and the sampling period.

Exemplarily, the confidence level may also be called evaluation accuracy, which is used to evaluate the quality of the track points, or the reliability of the track points. For example, if the position of the first trajectory point and the position of the second trajectory point differ by 10 meters, or the speed differs by 10 m/s, and the first trajectory point is a credible trajectory point, that is, the confidence degree satisfies the confidence degree range, then the first trajectory point The confidence of the second trajectory point is low, and the corresponding confidence score will exceed the confidence score range. Optionally, if the confidence is lower, the confidence score is lower, and the deviation between the position, direction and/or speed of the corresponding trajectory point and the actual trajectory point is larger, and the specific scoring rules can be set according to actual needs. limited.

Exemplarily, the altitude represents the altitude corresponding to the position to which the current watch belongs.

Step 103, the smart watch sends motion track information to the mobile phone.

Exemplarily, after acquiring the motion track information, the smart watch sends the motion track information to the mobile phone.

Optionally, if the smart watch also obtains other information in step 102, such as health information, etc., it may be sent to the mobile phone together with the motion track information.

Step 104, the mobile phone corrects the motion trajectory based on the road network data.

Exemplarily, as described in step 101, the mobile phone obtains the road network data in advance, and the mobile phone can obtain the road network data within the area to which the motion track belongs based on the received position information of each track point of the motion track. Exemplarily, The area is a rectangular area with a range of 5 km*5 km, or a circular area with a radius of 5 km with any trajectory point on the motion trajectory as the center, or the centroid of multiple trajectory points on the motion trajectory, and the centroid It is a circular area with a center and a radius of 5 kilometers.

Exemplarily, the mobile phone may correct the motion trajectory based on the acquired road network data (also referred to as deviation correction, correction or calibration). For example, the road network data includes but is not limited to data such as the width, position (latitude and longitude) and length of the road. Figure 7a is a schematic diagram of the motion trajectory before the deviation correction displayed by the mobile phone. The motion trajectory displayed by the mobile health application is Based on the road network data obtained by the mobile phone, it is assumed that the mobile phone displays the motion trajectory before deviation correction. As can be seen in Figure 7a, there are multiple trajectory points on the motion trajectory that deviate from the road. As mentioned above, the mobile phone can correct the track points that deviate from the road based on the road network data of the road, so that the deviated track points can be restored to the road, so that each track point on the motion track is always kept on the road, as shown in the figure 7b is a schematic diagram of the movement trajectory after the deviation correction displayed by the mobile phone.

Optionally, if each trajectory point on the motion trajectory is located on the road, the motion trajectory need not be corrected.

Step 106, the mobile phone displays the motion track.

Exemplarily, the sports health application of the mobile phone displays the corrected motion trajectory. Optionally, the sports health application can also display health information and the like.

Due to the limitation of the antenna performance of the smart watch, there may be a large deviation between the motion track obtained by the smart watch and the actual motion track. For example, the track point is not on the road. When the mobile phone obtains the road network data, the mobile phone can realize Correction of motion trajectories sent by smartwatches. However, since the road network data is artificially generated, if the actual road is changed, if the road network data cannot be manually updated in time, the road network data obtained by the mobile phone within the area to which the road belongs will be inaccurate. . In addition, road network data usually only covers main roads, and cannot cover internal roads such as sports fields and parks. Therefore, if the mobile phone fails to obtain the road network data within the area to which the motion trajectory belongs, or the obtained road network data is inaccurate, the mobile phone cannot correct the motion trajectory, and can only display the obtained intelligent The movement trajectory sent by the watch, such as the result shown in Figure 7a. For example, assuming that a new road is built on the open space A, but the road network data cannot be updated in time, in the road network data stored in the mobile phone, the road network data corresponding to the open space A still indicates that the land is an open space. Suppose the user wears a smart watch to run on the newly built road in the open space A. Since the mobile phone cannot obtain the road network data of the road, the mobile phone cannot correct the motion trajectory sent by the received smart watch, and can only display the smart watch. Sending motion traces with poor accuracy.

In order to solve the above problems, the present application provides a trajectory correction method, which can realize the correction of the motion trajectory of the smart watch without relying on road network data, so as to effectively improve the accuracy of the motion trajectory displayed by the application and improve the user experience. .

scene one

With reference to FIG. 1, FIG. 8 shows a schematic flowchart of a trajectory correction method provided by an embodiment of the present application. Referring to FIG. 8, specifically, the trajectory correction method of the present application may include standard path training, standard path download, standard path There are four parts of matching and track correction, and the above four parts are described in detail below.

Part 11. Standard Path Training.

Specifically, the cloud can be used to train motion trajectories uploaded by one or more terminals to obtain a standard path. FIG. 9 is an exemplary schematic flowchart of standard path training. Referring to FIG. 9 , specifically, mobile phone 1, mobile phone 2, and mobile phone 3 can send motion tracks 1 to 5, motion tracks 6, and motion tracks 7 to the cloud, respectively. 10. The cloud stores the received motion trajectories 1 to 10 in the storage unit. Exemplarily, the training unit in the cloud can obtain motion trajectories (for example, motion trajectories 1 to 10) stored within a week from the storage unit every other week (ie, 7 days). Train to get one or more standard paths.

In a possible implementation manner, the mobile phone 1, the mobile phone 2, and the mobile phone 3 may send the motion trajectory to the cloud in the same or different periods. For example, mobile phone 1 can send motion tracks 1 to 5 to the cloud in the first cycle, mobile phone 2 can send motion track 6 to the cloud in the second cycle, and mobile phone 3 can send motion tracks 7 to 10 to the cloud in the third cycle. Not limited.

In a possible implementation manner, the training unit may periodically acquire the motion trajectory within the period from the storage unit for training. Exemplarily, the cycle duration may be 7 days or 3 days, and the cycle duration described in this application is only an illustrative example, which is not limited in this application.

In another possible implementation manner, the training unit may also acquire untrained motion trajectories from the storage unit aperiodically. For example, every time the storage unit receives 1000 motion trajectories, the training unit is notified to perform training.

Section 12, Standard Path Downloads.

FIG. 10 is a schematic flowchart of downloading a standard path. Referring to FIG. 10 , specifically, after the training unit in the cloud obtains the standard path, it outputs the standard path to the storage unit for storage. Mobile phone 1 to mobile phone 3 (including mobile phone 1, mobile phone 2 and mobile phone 3) can download the standard path on demand.

Exemplarily, the standard path download rules on the mobile terminal include but are not limited to:

1) The mobile phone is downloaded once per cycle (7 days).

2) Download the standard path within the specified area each time.

In a possible implementation manner, the download period of the mobile phone may be 7 days or 3 days, which is not limited in this application.

In a possible implementation manner, the specified area range may be the area range to which the place where the user often runs (for the concept of the area range, refer to the description in step 104, which will not be repeated here). Exemplarily, the specified area range may also be the area range to which the place where the user ran most recently belongs. Optionally, in order to reduce the amount of stored data, the number of designated area ranges can be 7 online. For example, the mobile phone only updates the 7 places where the user recently ran every week (assuming that the user runs at a different place each time) belonging to the designated area. geographic range.

Exemplarily, the standard path download method on the mobile phone terminal may also be that after the user clicks on the sports health application, the mobile phone responds to the user's click operation, obtains the current location of the mobile phone, and updates the standard path within the area where the mobile phone is located. Exemplarily, the sports health application can provide a search function. The user can search for a specified location in the search function, such as the XX park, and select a standard path in the XX park to download. The mobile phone detects the user's operation behavior and can request it from the cloud. The standard route in the XX campus, the cloud can send the standard route in the XX campus to the mobile phone. Exemplarily, if one or more standard routes in the XX park have been stored in the mobile phone, the mobile phone can detect whether the stored standard routes are the standard routes obtained recently (for example, within 7 days), if one or more standard routes are If it is obtained within 7 days, the mobile phone can request the cloud for other standard routes in the XX campus in addition to the one or more standard routes that have been saved.

Exemplarily, the standard path download method on the mobile phone terminal may also be that the cloud actively pushes the standard path within the specified area to the mobile phone terminal. For example, the cloud can record the specified area range corresponding to the mobile phone, and after detecting that there is an updated standard path within the specified area, push the standard path within the specified range to the mobile phone, or the cloud can also periodically (for example, 7 days) ) pushes the standard path within the specified area to the mobile terminal, and when the user confirms that the download is allowed, the mobile phone obtains the standard path pushed by the cloud.

Section 13, Standard Path Matching.

Figure 11 is a schematic flow chart of standard path matching and trajectory correction. Referring to Figure 11, exemplarily, a user wears a smart watch to run. During the running process, the smart watch obtains the user's movement information, including but not limited to the movement information on the movement track 11. Information such as position, direction, velocity, confidence, and altitude of track points. After the user goes home, the smart watch can be paired with the mobile phone 1 via Bluetooth. After the smart watch and the mobile phone 1 establish a Bluetooth connection in response to the user's operation, application pairing can be performed. Figure 12 is a schematic diagram of application pairing. , the display window of the mobile phone displays the main page, and the main page includes one or more spaces, such as application icons, battery controls, etc., the user can click the sports health application icon, the mobile phone detects the user's click operation, and displays the sports health on the display window. The application interface, the sports health application interface includes one or more plug-ins, the user can click the "device" option, the mobile phone detects the user's click operation, and displays the device interface. Optionally, the device interface includes one or more prompt boxes, the prompt box may include prompt information, and the prompt information is used to indicate that "multiple devices can be added", and may also include other prompt boxes. For example, another prompt box includes a prompt. The message "helps you easily play with Huawei wearable devices". The user can click the "Add Device" prompt box, the mobile phone detects the user's click operation, and displays the Add Device Interface (also called the All Device Interface), which includes one or more device options, and the user can click the "Watch" option. . The mobile phone detects the user's click operation and displays the watch interface. Optionally, the watch interface can provide one or more series options of Huawei watches. The user can click the HUAWEI WATCH GT2 series. It should be noted that the brands shown in the figure and The series are only illustrative examples, and are not limited in this application. Exemplarily, the mobile phone detects the user's click operation, and displays the HUAWEI WATCH GT2 series pairing interface. Exemplarily, the interface includes one or more controls, such as multiple controls at the bottom (including options such as health, exercise, and equipment), It also includes a "start pairing" option, the user can click the "start pairing" option, the mobile phone detects the user's click operation, and pairs with the model corresponding to the user's smart watch (for example, Huawei Smart Watch 4).

Optionally, the mobile phone and the smart watch have the same user account, and the user can log in to the same account on the mobile phone and the smart watch. Optionally, after the mobile phone and the smart watch are successfully paired for the first time, the smart watch approaches the mobile phone again. If the mobile phone and the smart watch have the same account, the mobile phone and the smart watch can be automatically connected.

Still referring to FIG. 11 , after the smart watch is successfully paired with the mobile phone 1 (referring to Bluetooth pairing and application pairing), the smart watch can send the motion track 11 to the mobile phone 1 through the Bluetooth connection. After acquiring the motion track 11, the mobile phone 1 matches the motion track 11 with one or more downloaded standard paths one by one, and obtains a successfully matched standard path.

Part 14, track deviation correction.

Specifically, still referring to FIG. 11 , after the mobile phone 1 obtains the standard path matching the motion trajectory 11 , the mobile phone 1 can rectify the motion trajectory 11 based on the standard path.

To sum up, compared with the prior art in which the mobile phone needs to rely on the road network data to rectify the motion trajectory, in the present application, the cloud can perform group motion trajectory training based on the obtained multiple motion trajectories to obtain a standard path. , the mobile phone can obtain the standard path matching the motion trajectory from the cloud, so as to correct the motion trajectory based on the standard path, so as to propose a deflection correction method that does not depend on the road network data, and effectively improve the accuracy and reliability of the motion trajectory correction. , so as to improve the user experience.

The following uses several specific embodiments to describe in detail each part in the above method embodiment.

Scenario: Mobile phone 1 acquires motion track information 1 to 5 in the first cycle, and sends motion track information 1 to 5 to the cloud in the first cycle. The motion trajectories 1 to 5 are generated by user 1 running counterclockwise in the park A at different time periods in the first cycle. It should be noted that, in the following embodiments, the cycle duration is one week (ie, 7 days) as an example for description, the first cycle can be understood as the first week, and the second cycle can be the next cycle adjacent to the first cycle. a week. In other embodiments, the second period may also be another week separated from the first period, which is not limited in this application.

The mobile phone 2 acquires the motion track information 6-9 in the first cycle, and sends the motion track information 6-9 to the cloud in the first cycle. The motion trajectories 6 to 9 are generated by the user 2 running in the counterclockwise direction in the park B at different time periods in the first cycle.

The mobile phone 3 acquires the motion track information 10 in the second cycle, and sends the motion track information 10 to the cloud in the second cycle. The motion trajectory 10 is generated by the user 3 running in the clockwise direction in the park A in the second cycle.

Each motion track information includes, but is not limited to: the position, direction, speed, confidence and height of each track point on the motion track, and optionally, also includes identification information of the mobile phone. Optionally, the identification information of the mobile phone can be information such as the serial number of the mobile phone, and the purpose of sending this information is to enable the cloud to identify whether the generator of the acquired motion trajectory information is a device of a specified type based on the identification information of the mobile phone, For example, mobile phones, etc., it can also be understood that a specified type of device refers to a device whose acquired motion trajectory can be used as the basis for standard path training, while a non-specified type of device refers to a smart watch, smart watch and other motion trajectories that cannot be used as a generation standard. Path based device. For example, some parameters in the mobile phone serial number can be used to indicate the type of the device. For example, if the mobile phone is a Huawei P30, the cloud can determine that the Huawei P30 mobile phone is the specified type based on the correspondence between the preset serial number parameters and the specified type of device. equipment.

Optionally, the identification information of the mobile phone can also be a special symbol in the specified field. For example, the data field in the data packet sent by the mobile phone to the cloud can include an indication field. When the value in the indication field is "1" , indicating that the sender of the data packet is a mobile phone, that is, a device of a specified type. Correspondingly, the data field in the data packet sent by the watch to the cloud may include an indication field. When the value in the indication field is "0", the identification data The sender of the packet is a watch, that is, a device of a non-specified type.

The training method in the cloud will be described in detail below in conjunction with the above scenarios. FIG. 13 shows a schematic flowchart of the standard path training provided in this embodiment of the present application. Referring to FIG. 13 , it specifically includes:

Step 201, the cloud determines whether the motion track information 1-9 is generated by a device of a specified type.

Exemplarily, at the end of the first cycle, the cloud (unless otherwise specified, the execution subject hereinafter refers to the training unit in the cloud) extracts the motion trajectory information 1-9 obtained in the first cycle from the storage unit.

Exemplarily, the cloud may determine, based on the identification information included in each motion track information, whether the generator of the motion track is a device of a specified type (for the concept, refer to the above). Exemplarily, in this embodiment, the cloud determines, based on the identification information, that the generators of the motion trajectories 1 to 9 are all mobile phones, and executes step 202 .

In a possible implementation manner, the mobile phone may send the received motion track sent by the smart watch to the cloud, so as to instruct the cloud to store the motion track obtained by the smart watch before deviation correction. In this example, taking the mobile phone 1 as an example, when the mobile phone 1 sends the motion track of the smart watch, it needs to carry an identifier used to indicate that the motion track is generated by the smart watch, for example, it can be the serial number of the smart watch or carried in the indication field Special identification (refer to the above), the cloud can determine the generation end of the motion track is a smart watch based on the corresponding relationship between the serial number or the special representation and the specified type of equipment, and then store the motion track.

In another possible implementation, if an electronic device such as a smart watch or a smart bracelet has a cellular communication function, that is, data can be exchanged with the cloud through a cellular network. The track and the serial number of the smart watch are sent to the cloud. Similarly, the cloud can determine the generation end of the motion track as the smart watch based on the serial number, and store the motion track.

In another possible implementation, if the smart watch is a motion track generated by a positioning system based on a mobile phone, after the mobile phone obtains the motion track sent by the smart watch, the motion track information sent to the cloud includes an indication that the motion track is a smart watch. Generated by a mobile phone-based positioning system. For example, a user runs with a mobile phone and a smart watch, and the smart watch and the mobile phone always maintain a Bluetooth connection. The mobile phone can obtain the motion track based on the mobile phone's positioning system and transmit it to the smart watch. The smart watch combines the motion track and health information to generate sports health information. (including motion trajectory information and health information), after the smart watch reports the motion health information to the mobile phone, the mobile phone can send the motion trajectory information to the cloud, where the information includes an identifier indicating that the motion trajectory is sent by the mobile phone-based positioning system. In this example, the cloud can use this type of motion trajectory as a training sample to train the standard path.

Step 202, the cloud detects whether there is a standard path matching the motion trajectories 1-9.

Specifically, based on the location information of the motion track, the cloud extracts one or more standard paths within the area to which the stored motion track belongs to perform similarity matching to determine whether there is a standard path corresponding to the motion track, for example, motion track 1 The area to which ~5 belongs is park A, and the area to which motion tracks 6 to 9 belong is park B.

The specific process of similarity matching is described in detail below:

FIG. 14 is an exemplary schematic flowchart of similarity matching. Referring to FIG. 14 , exemplarily, taking the matching between the motion track A and the motion track B as an example, the track points on the motion track stored in the cloud All are stored in the order of the generation time of the trajectory points, that is to say, after the mobile phone obtains the trajectory points according to the sampling period, the motion information of each trajectory point in the trajectory information sent to the cloud is still in accordance with each trajectory point. Generate (or get) sent sequentially. In the process of similarity matching, the cloud performs similarity matching on each trajectory point according to the order of the trajectory points, wherein the order of the trajectory points refers to the temporal order of each trajectory point on the motion trajectory. Exemplarily, taking the trajectory point 1 on the motion trajectory A as an example, the trajectory point 1 is the starting trajectory point on the motion trajectory A (that is, the trajectory point recorded for the first time), and the cloud is based on the direction 1 of the trajectory point 1, Traverse each track point on the motion track B, and obtain the track point whose included angle with the direction 1 is less than 30°. It should be noted that, the traversal process is also in accordance with the order of each track point on the motion track B. Optionally, the cloud can traverse from the point 1' of the trajectory based on the sequence of each trajectory point on the motion trajectory B, and only traverse 80 (the specific value can be set according to actual needs) trajectory points to reduce the power of the cloud server. consumption. Exemplarily, after point-by-point matching, the trajectory points obtained by the cloud whose included angle between the motion trajectory B and the direction 1 of trajectory point 1 is less than or equal to 30° include trajectory point 1', trajectory point 2', trajectory point 1', and trajectory point 1'. 3'. It should be noted that the thresholds described in the embodiments of the present application, for example, the angle between directions, and the distance thresholds described below are all illustrative examples, and in other embodiments, other values may also be used For example, the threshold value of the included direction angle may be 40°, etc., which is not limited in this application. It should be further noted that the range of the angle between the two directions is [0, 180°]. For example, the angle between the direction 1 and the direction 2 is 28°, and the angle between the direction 1 and the direction 3 is 28°. is 10°, and the angle between direction 1 and direction 4 is 12°.

Exemplarily, after direction matching, the cloud performs distance matching between the trajectory point 1 and each point in the trajectory point set (including trajectory point 1', trajectory point 2', and trajectory point 3') whose directions are successfully matched, and selects the point corresponding to the trajectory. The trajectory point with the closest distance between points 1 is the projection point corresponding to the trajectory point 1. Exemplarily, the cloud matches the trajectory point 1 with the trajectory points in the trajectory point set one by one, and obtains the distances between the trajectory point 1 and the trajectory point 1', the trajectory point 2', and the trajectory point 3' respectively: distance 1, Distance 2, Distance 3. After comparison, the cloud determines that the distance 1 is the minimum of several distance values, that is, the distance between the trajectory point 1 and the trajectory point 1' is the closest, and the trajectory point 1' is the projection point of the trajectory point 1. Optionally, the distance value is obtained based on the position of the trajectory point.

Exemplarily, after the projection point is determined, the cloud determines whether the projection point meets the set condition. Exemplarily, the set condition is that the distance is less than or equal to 50 meters. In an example, if the cloud detects that the distance 1 is less than 50 meters, for example, the distance 1 is 10 meters, the cloud determines that the trajectory point 1' is a projection point corresponding to the trajectory point 1 that meets the set conditions.

Exemplarily, the cloud continues to sequentially match each trajectory point on the motion trajectory A in the above-mentioned manner. It should be noted that, if the projection point corresponding to the trajectory point 1 is the trajectory point 2', then after the trajectory point 1 is matched For example, when matching the trajectory point 2, it can only be traversed from the trajectory point 3' to select the corresponding projection point. It should be noted that the above-mentioned trajectory point 2 after the trajectory point 1 refers to the time sequence, that is, when the trajectory is generated, the trajectory point 1 is generated first, and then the trajectory point 2 is generated. It should be further noted that starting the traversal from the trajectory point 3' means starting the traversal from the adjacent trajectory point (that is, the trajectory point 3') behind the trajectory point 2' that matches the trajectory point 1.

Exemplarily, if 70% of the trajectory points on the motion track A all have projection points that meet the set conditions on the motion track B, it is determined that the motion track A and the motion track B are successfully matched, which can also be understood as the motion track A. The similarity with the motion trajectory B is greater than or equal to 70%. It should be noted that the similarity matching method described in this application is only a schematic example, and in other embodiments, similarity matching can also be performed in other ways. The point with the smallest corresponding distance is the projection point, and then based on the direction and distance between each projection point and the trajectory point, it is determined whether the projection point meets the conditions, etc., which is not limited in this application.

Still referring to FIG. 13 , exemplarily, after the cloud matches the motion trajectories 1 to 5 with the standard paths in the park A stored in the storage unit one by one, it is determined that there is no standard path matching the motion trajectories 1 to 5, and the same is not detected. Step 203 is executed for the standard paths matching the motion trajectories 6-9.

Step 203, the cloud generates a standard path.

Exemplarily, Figure 15 is a schematic diagram of generating a standard path based on motion trajectories 1 to 5. It should be noted that, before generating a standard path, the cloud also matches motion trajectories 1 to 5 in pairs to determine the motion trajectories. 1 to 5 are motion trajectories with a similarity greater than or equal to 70%, that is, only multiple motion trajectories with a similarity greater than or equal to 70% can be used as samples for standard path generation training.

Exemplarily, the cloud uses the hierarchical clustering method to train multiple motion trajectories. Referring to FIG. 15 , the cloud corrects the deviation of the motion trace 1 and the motion trace 2, and obtains the correction result 1; Correction result 2 is obtained; correction of motion trajectory 5 and correction result 2 is performed, correction result 3 is obtained; correction result 1 and correction result 3 are corrected, correction result 4 is obtained, and correction result 4 corresponds to motion trajectory 1 to 5. Standard route, which can be marked as standard route A1 in campus A. It should be noted that in the process of correction, the position, direction and speed of each track point are corrected, and the saved information includes the position, direction and speed of each track point on the corrected motion track 4 corresponding to the correction result 4 .

It should be noted that this application only takes the hierarchical clustering method as an example for description, and in other embodiments, other algorithms or methods may also be used to determine the standard path, which is not limited in this application.

The deviation correction process will be described in detail below. FIG. 16 is a schematic diagram of the deviation correction process exemplarily shown. Referring to FIG. 16 , exemplarily, in the process that the cloud performs deviation correction based on the motion track A and the motion track B, the cloud still follows the above The similarity matching method described in this paper determines the projection points corresponding to the trajectory points of the motion trajectory A on the motion trajectory B, and uses the trajectory point 1 on the motion trajectory A and the projection point on the motion trajectory B corresponding to the trajectory point 1 ( The track point 1') is used as an example to illustrate, assuming that the position corresponding to the track point 1 is the position 1, the position corresponding to the track point 1' is the position 2, and the corrected position 1 of the corrected track point 1 is the position 1 and the position 2. The direction, speed, confidence and height of the corrected trajectory point 1 are also obtained based on the direction and speed of the trajectory point 1 ′ and the trajectory point 1 . It should be noted that the centering correction method in the above example is only applicable to the correction between two motion trajectories with the same heat, where the heat refers to the number of training samples that generate a standard path or correction result. For an example, see Figure 15 , the correction result 1 is generated based on the motion track 1 and the motion track 2, and its popularity (that is, the number of training samples) is 2. Correspondingly, the popularity of the correction result 3 is 3 (including the motion track 3, the motion track 4 and the motion track 2). track 5). Exemplarily, when correcting correction result 1 and correction result 3, since correction result 3 is hotter than correction result 1, the position of each track point on correction result 4 is closer to correction result 3. Exemplarily, The ratio of the heat of the correction result 1 to the heat of the correction result 3 is 2:3, and the deviation is corrected according to this ratio during the correction process. The cloud rectifies the position, direction and speed of each corresponding trajectory point (that is, the correspondence between the trajectory point and the projection point) on the motion trajectory A and the motion trajectory B, so as to obtain the motion corresponding to each corrected trajectory point. information, that is, the correction track information corresponding to the correction motion track.

Exemplarily, as shown in FIG. 17 is a schematic diagram of generating standard paths based on motion trajectories 6 to 9. The cloud also trains motion trajectories 6 to 9 based on the hierarchical clustering method to generate the standard path B1 in the park B and the corresponding sports information.

In a possible implementation manner, the generation of the standard path may also adopt manual intervention. For example, any one of the multiple motion trajectories may be manually selected as the standard path. Optionally, the cloud records the standard path as manual. generated after intervention.

Step 204, the cloud saves the standard path information.

Specifically, the cloud saves the standard path information, that is, including the position, direction, speed, confidence, and height of each trajectory point on the standard path A1, and the position, direction, speed, and confidence of each trajectory point on the standard path B1. and height.

In a possible implementation manner, if in step 202, the cloud obtains a standard path (assuming a standard path X) that matches the motion trajectories 1 to 5, the cloud updates the standard path X based on the motion trajectories 1 to 5 . Exemplarily, the cloud still corrects the motion trajectories 1 to 5 two by two according to the method shown in FIG. 15 , and corrects the correction result 4 and the standard path X, and the correction method can still refer to the above. Optionally, the cloud can also record the popularity of the standard path X and the popularity of the correction result 4 (the concept of popularity is described above). For example, the popularity of the standard path X is 100, and the popularity of the correction result 4 is 5 ( That is, the motion trajectories 1 to 5), when correcting the correction result 4 and the standard path X, the correction is performed according to the ratio of 100:5, that is, the standard path X' after the correction is closer to the standard path X. It should be noted that, as mentioned above, the standard path may be generated by manual intervention. For this type of standard path, it does not need to be updated. That is to say, even if a matching motion trajectory is obtained, it will not be based on motion Trajectories update standard paths generated by human intervention.

FIG. 13 shows the process of training the motion trajectory obtained in the first cycle. The following describes the process of training the standard path in the second cycle. FIG. 18 is a schematic flowchart of the standard path training provided in this embodiment of the present application. Unless otherwise specified, the relevant content involved in this embodiment is the same or similar to the relevant content in FIG. 13 , and is not repeated here. Repeat. Referring to Figure 18, it specifically includes:

Step 301, the cloud determines whether the motion track information 6 is generated by a device of a specified type.

Step 302 , the cloud detects whether there is a standard path matching the motion track 6 .

Exemplarily, as shown in FIG. 19 , the cloud extracts the standard path within the area to which the motion track 6 belongs (ie, the park A), that is, the standard path A1 . The cloud matches the similarity between the motion track 6 and the standard path A1, and determines that the similarity between the motion track 6 and the standard path A1 is 0. For the specific matching process, reference may be made to the relevant content in step 202, which is not repeated here.

Step 303, the cloud generates a standard path.

Exemplarily, since the cloud does not detect a standard path matching the motion trajectory 6 and other motion trajectories, the motion trajectory 6 can be used as the standard path B1 in the park A.

Step 304, the cloud saves the standard path.

Exemplarily, the mobile phone 1 downloads the standard path A1 , the standard path A2 , and the standard path A3 from the cloud, and the specific download rules can be referred to above, which will not be repeated here.

FIG. 20 is a schematic flowchart of another trajectory deviation correction method provided by an embodiment of the present application. Referring to FIG. 20 , it specifically includes:

Step 401, the mobile phone acquires one or more pieces of motion track information.

Step 402, the mobile phone generates a standard path based on one or more motion trajectories.

As given by you, the mobile phone can be trained based on one or more motion trajectories to generate a corresponding standard path. For the generation method of the standard path, please refer to the relevant content of step 203, which will not be repeated here.

Step 403, the mobile phone sends the standard path information to the cloud.

Step 404, the cloud performs training based on the standard path samples sent by one or more mobile phones to generate a standard path.

Exemplarily, one or more mobile phones can send one or more standard paths generated by them to the cloud. For the cloud, the standard paths sent by each mobile phone are the standard path training samples, and the cloud can perform training based on the standard path training samples to generate For the standard path, reference may be made to step 203 for the method of generating the standard path, which will not be repeated here.

Step 405, the cloud saves the standard path information.

The following is a detailed description of the trajectory correction method with reference to the schematic flowchart of the trajectory correction method provided by the embodiment of the present application shown in FIG. 21 . After acquiring the motion track 11, after the smart watch and the mobile phone 1 are successfully paired by Bluetooth and the application, the smart watch sends the motion track 11 to the mobile phone 1 through the Bluetooth connection. specific:

In step 501, the mobile phone 1 determines whether a standard path within the area to which the motion track 11 belongs is stored.

Exemplarily, the mobile phone 1 extracts a standard path within the area to which the motion track 11 belongs (ie, the park A), including the standard path A1 and the standard path A2, based on the position of each track point of the motion track 11 .

In a possible implementation manner, if the mobile phone 1 determines that the standard path within the area to which the motion track 11 belongs is not stored, the mobile phone 1 downloads the standard path in the park A from the cloud. Exemplarily, if the cloud does not store the standard path in the park A, the mobile phone 1 directly displays the motion track 11 .

Step 502, the mobile phone 1 determines whether the standard path A1 and the standard path A2 are the latest standard paths.

Exemplarily, as described above, the mobile phone 1 will periodically update the saved standard path, and the mobile phone 1 determines whether the standard path A1 and the standard path A2 are the standard paths updated in the latest cycle. A1 and standard route A2 are standard routes updated in the latest cycle, and step 503 is executed. In another example, if standard route A1 and standard route A2 are not the standard routes updated in the latest cycle, mobile phone 1 downloads the park from the cloud Standard path within A.

Step 503, the mobile phone 1 performs similarity matching between the motion track 11 and the standard path A1 and the standard path A2.

Exemplarily, the mobile phone 1 performs similarity matching between the motion track 11 and the standard path A1, and obtains that the similarity between the motion track 11 and the standard path A1 is greater than 70%, and the mobile phone 1 determines that the motion track 11 matches the standard path A1.

In a possible implementation manner, if both the standard path A1 and the standard path A2 do not match the motion track 11 , the mobile phone 1 displays the motion track 11 .

In step 504, the mobile phone 1 corrects the motion track 11 based on the standard path A1.

Exemplarily, referring to FIG. 22 , the mobile phone can rectify the motion track 11 based on the standard path A1 , and the motion track 11 after the rectification is shown in FIG. 22 .

It should be noted that, unlike the deviation correction in FIG. 16 , in the deviation correction process of step 504, the mobile phone 1 only checks that the distance between the trajectory point on the motion trajectory 11 and the corresponding projection point on the standard path is less than or equal to 50 The track points whose direction angle is less than or equal to 30° will be corrected, and the track points that meet the above conditions will be corrected by 75% to the corresponding projection points during the correction process. Make corrections. For example, assuming that the distance between the trajectory point on the motion trajectory 11 and the projection point on the standard path A1 is 10 meters, the distance between the corrected trajectory point and the projection point is 2.5 meters, and the correction of the direction and speed is related to the position. The modifications are similar, and will not be repeated here, and other details can still refer to the related description in FIG. 16 , which will not be repeated here.

Exemplarily, for trajectory points that do not meet the above conditions, that is, the distance between the trajectory point and the projection point is greater than 50 meters and/or the included angle of the direction is greater than 30°, the cloud further determines whether the trajectory point is a jump trajectory point, wherein , the jump trajectory point refers to the large deviation between the position or direction of the trajectory point and the previous trajectory point.

In an example, if there is no jump track point on the motion track 11, that is, as shown in Figure 23a, although the distance between some track points and the projected point on the standard path A1 is greater than 50 meters, such track points are Slowly changing, that is, there is no sudden jump in the position and direction between each track point and the previous track point. Therefore, for this type of track point, the mobile phone 1 does not perform deviation correction. For example, during the running process, the user detours from a certain path to form a trajectory point corresponding to the protruding part in the motion trajectory 11. During the deviation correction process, the mobile phone 1 ignores this part of the trajectory point, that is, the deviation correction is not performed on these trajectory points. The track points are still retained, and the mobile phone displays the motion track 11 after the deviation correction as shown in Figure 24. It should be noted that the outdoor running interface in Figure 24 can refer to Figure 12. The mobile phone detects that the user clicks the "Motion" option at the bottom to display the outdoor The running interface, referring to FIG. 24 , exemplarily, the outdoor running interface includes one or more controls, for example, including a track control (that is, a "track" option). After the user clicks on the "track" option, the mobile phone can respond to the user's click operation, On the outdoor running interface, display the corrected motion trajectory and other sports information, such as kilometers, time (referring to the time when the watch generates the motion trajectory), exercise time (it can also be understood as exercise duration), average pace, heat, etc. information. Optionally, if the map in the area to which the motion track belongs (that is, the road network data described above) is stored in the mobile phone, the mobile phone can perform corresponding processing on the map and the motion track after the deviation correction, so that the corresponding area on the map can be stored in the mobile phone. The motion track after correction is displayed inside.

In another example, if there is a jump track point on the motion track 11, as shown in Figure 23b, the mobile phone 1 deletes this type of track point during the deviation correction process, and deletes the previous track point and the next track point of the track point. Click to connect, and the movement track after deviation correction displayed by the mobile phone is shown in Figure 25.

Step 505, the mobile phone 1 displays the motion track 11 after the deviation correction.

The above method embodiments are all described based on the mobile phone online scenario, and the mobile phone online means that the mobile phone can obtain the standard path from the cloud. The technical solutions in the embodiments of the present application can also be applied to the offline scenario of the mobile phone, that is, the scenario where the mobile phone cannot obtain the standard path from the cloud, as shown in FIG. Taking the grassland scene as an example, the user runs in an area on the grassland with a mobile phone. Suppose that the user runs 4 laps along the same trajectory in a period of time, and the corresponding motion trajectories are Motion Track 12 to Motion Track 15. . Similar to the cloud, the mobile phone can include a storage unit and a training unit, the mobile phone can save the motion trajectories 12-15, and the training unit can extract the motion trajectories 12-15 from the storage unit for training to obtain a standard path.

Exemplarily, the duration of the training cycle on the mobile phone terminal may be one day, that is, the motion trajectory obtained by the storage unit is trained every other day, or the training process may be performed in response to user instructions and based on user instructions.

Exemplarily, the mobile phone may calculate the confidence level of each motion track based on the confidence level of each track point, and the confidence level of the motion track may be the sum of the confidence levels of each track point. The trajectory is more accurate, that is, the closer it is to the actual trajectory. The mobile phone can select any of the motion trajectories with the highest confidence as the standard path. Optionally, the mobile phone can also train the motion trajectories 12 to 15 based on the same training method as the cloud (ie, the relevant content of step 203 ) to obtain the standard path.

Still referring to FIG. 17 , the training unit sends the acquired standard path to the storage unit.

Exemplarily, the user wears the smart watch to run along the above-mentioned track, and the smart watch obtains the motion track information 16 , including the position, direction, speed, confidence and height of each track point on the motion track 16 . The smart watch sends the motion track information 16 to the mobile phone, and the matching unit in the mobile phone can obtain a standard path matching it based on the motion track 16 , and the deviation correction unit can correct the deviation of the motion track 16 based on the matched standard path. It should be noted that, unless otherwise specified, the steps performed by the mobile phone in the offline scenario are similar to the steps performed by the cloud and the mobile phone in the online scenario, and are not repeated here.

It can be understood that, in order to realize the above-mentioned functions, the electronic device includes corresponding hardware and/or software modules for executing each function. The present application can be implemented in hardware or in the form of a combination of hardware and computer software in conjunction with the algorithm steps of each example described in conjunction with the embodiments disclosed herein. Whether a function is performed by hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functionality for each particular application in conjunction with the embodiments, but such implementations should not be considered beyond the scope of this application.

In this embodiment, the electronic device can be divided into functional modules according to the above method examples. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above-mentioned integrated modules can be implemented in the form of hardware. It should be noted that, the division of modules in this embodiment is schematic, and is only a logical function division, and there may be other division manners in actual implementation.

Exemplarily, Fig. 27 shows a schematic block diagram of an apparatus 200 according to an embodiment of the present application. The apparatus 200 may include: a processor 201, a transceiver/transceiver pin 202, and optionally, a memory 203.

Various components of the device 200 are coupled together through a bus 204, wherein the bus 204 includes a power bus, a control bus and a status signal bus in addition to a data bus. For clarity, however, the various buses are referred to as bus 204 in the figures.

Optionally, the memory 203 may be used for instructions in the foregoing method embodiments. The processor 201 can be used to execute the instructions in the memory 203, and control the receiving pins to receive signals, and control the sending pins to send signals.

The apparatus 200 may be a mobile phone, a smart watch, or a server in the cloud in the foregoing method embodiments.

Wherein, all relevant contents of the steps involved in the above method embodiments can be cited in the functional descriptions of the corresponding functional modules, which will not be repeated here.

This embodiment also provides a computer storage medium, where computer instructions are stored in the computer storage medium, and when the computer instructions are run on an electronic device or a network device (such as a cloud server), the electronic device executes the above-mentioned related method steps to achieve the above-mentioned The track deviation correction method in the embodiment.

This embodiment also provides a computer program product, which when the computer program product runs on the computer, causes the computer to execute the above-mentioned relevant steps, so as to realize the trajectory deviation correction method in the above-mentioned embodiment.

In addition, the embodiments of the present application also provide an apparatus, which may specifically be a chip, a component or a module, and the apparatus may include a connected processor and a memory; wherein, the memory is used for storing computer execution instructions, and when the apparatus is running, The processor can execute the computer-executed instructions stored in the memory, so that the chip executes the track deviation correction method in each of the foregoing method embodiments.

Wherein, the electronic device, computer storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding method provided above. Therefore, for the beneficial effects that can be achieved, reference can be made to the corresponding provided above. The beneficial effects in the method will not be repeated here.

From the description of the above embodiments, those skilled in the art can understand that for the convenience and brevity of the description, only the division of the above functional modules is used as an example for illustration. In practical applications, the above functions can be allocated by different The function module is completed, that is, the internal structure of the device is divided into different function modules, so as to complete all or part of the functions described above.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or May be integrated into another device, or some features may be omitted, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

Units described as separate components may or may not be physically separated, and components shown as units may be one physical unit or multiple physical units, that is, may be located in one place, or may be distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

Any content of each embodiment of the present application and any content of the same embodiment can be freely combined. Any combination of the above is within the scope of this application.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application can be embodied in the form of software products in essence, or the parts that make contributions to the prior art, or all or part of the technical solutions, which are stored in a storage medium. , including several instructions to make a device (may be a single chip microcomputer, a chip, etc.) or a processor (processor) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read only memory (ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program codes.

The embodiments of the present application have been described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific embodiments, which are merely illustrative rather than restrictive. Under the inspiration of this application, without departing from the scope of protection of the purpose of this application and the claims, many forms can be made, which all fall within the protection of this application.

Claims

A trajectory correction system, comprising: a cloud server, a first electronic device and a second electronic device, the first electronic device is connected to the second electronic device through Bluetooth, and the first electronic device is connected to the second electronic device through a cellular The network performs data interaction with the cloud server;

The first electronic device is used for:

acquiring the first motion track and the second motion track within the first area, and sending the first motion track and the second motion track to the cloud server;

The cloud server is used for:

obtaining a third motion trajectory according to the received first motion trajectory and the second motion trajectory;

The first electronic device is used for:

obtaining the third motion trajectory from the cloud server;

The second electronic device is used for:

acquiring a fourth motion trajectory within the range of the first area;

sending the fourth motion trajectory to the first electronic device;

The first electronic device is also used for:

In response to the received fourth motion trajectory, the fourth motion trajectory is corrected based on the third motion trajectory, and the corrected fourth motion trajectory is displayed.
The system according to claim 1, wherein the system further comprises a third electronic device, and the third electronic device performs data interaction with the cloud server through a cellular network;

The third electronic device is used for:

acquiring a fifth motion trajectory within the range of the first area;

The cloud server is also used for:

receiving the fifth motion trajectory;

obtaining a sixth motion trajectory according to the fifth motion trajectory and the third motion trajectory;

The first electronic device is also used for:

obtaining the sixth motion trajectory from the cloud server;

The second electronic device is used for:

acquiring a seventh motion trajectory within the first area;

sending the seventh motion trajectory to the first electronic device;

The first electronic device is also used for:

In response to the received seventh motion trajectory, the seventh motion trajectory is corrected based on the sixth motion trajectory, and the corrected seventh motion trajectory is displayed.
The system according to claim 1, wherein the system further comprises a third electronic device, and the third electronic device performs data interaction with the cloud server through a cellular network;

The third electronic device is used for:

acquiring an eighth motion track and a ninth motion track within a second area range, where the first area range is different from the second area range;

The cloud server is also used for:

receiving the eighth motion trajectory and the ninth motion trajectory;

According to the eighth motion track and the ninth motion track, obtain a tenth motion track;

The first electronic device is also used for:

obtaining the tenth motion trajectory from the cloud server;

The first electronic device is also used for:

Perform similarity matching between the fourth motion trajectory and the third motion trajectory and the tenth motion trajectory, respectively, and determine that the fourth motion trajectory and the third motion trajectory are successfully matched for similarity;

Based on the third motion trajectory whose similarity is successfully matched, the fourth motion trajectory is rectified, and the rectified fourth motion trajectory is displayed.
The system according to claim 1, wherein the similarity between the first motion trajectory and the second motion trajectory is greater than or equal to a similarity threshold.
The system of claim 1, wherein the first electronic device is configured to:

receive instructions from users,

The third motion trajectory is acquired from the cloud server in response to the user's instruction.
The system according to claim 1, wherein the cloud server is used for:

Sending indication information to the first electronic device to indicate that the first electronic device can download the third motion trajectory from the cloud server.
The system according to claim 1, wherein the first electronic device is a mobile phone, and the second electronic device is a smart watch.
The system according to claim 1, wherein a sports health application is installed on the first electronic device and the second electronic device respectively.
The system according to claim 8, wherein the first electronic device is used for:

The fourth motion trajectory after the deviation correction is displayed on the application interface of the sports health application.
The system of claim 1, wherein the first electronic device and the second electronic device have the same user account.
A method for trajectory correction, characterized in that it is applied to a communication system, the system comprising: a cloud server, a first electronic device and a second electronic device, the first electronic device is connected to the second electronic device through Bluetooth, The first electronic device performs data interaction with the cloud server through a cellular network; the method includes:

obtaining, by the first electronic device, a first motion track and a second motion track within the first area, and sending the first motion track and the second motion track to the cloud server;

obtaining, by the cloud server, a third motion trajectory according to the received first motion trajectory and the second motion trajectory;

The first electronic device obtains the third motion trajectory from the cloud server;

acquiring, by the second electronic device, a fourth motion trajectory within the first area, and sending the fourth motion trajectory to the first electronic device;

In response to the received fourth motion trajectory, the first electronic device corrects the fourth motion trajectory based on the third motion trajectory, and displays the corrected fourth motion trajectory.
The method according to claim 11, wherein the system further comprises a third electronic device, and the third electronic device performs data interaction with the cloud server through a cellular network; the method further comprises:

acquiring, by the third electronic device, a fifth motion trajectory within the first area;

The cloud server receives the fifth motion trajectory, and obtains a sixth motion trajectory according to the fifth motion trajectory and the third motion trajectory;

The first electronic device obtains the sixth motion trajectory from the cloud server;

acquiring, by the second electronic device, a seventh motion track within the first area, and sending the seventh motion track to the first electronic device;

The first electronic device corrects the seventh motion trajectory based on the sixth motion trajectory in response to the received seventh motion trajectory, and displays the corrected seventh motion trajectory.
The method according to claim 11, wherein the system further comprises a third electronic device, and the third electronic device performs data interaction with the cloud server through a cellular network; the method further comprises:

The third electronic device acquires an eighth motion trajectory and a ninth motion trajectory within a second area, where the first area is different from the second area;

The cloud server receives the eighth motion track and the ninth motion track, and obtains the tenth motion track according to the eighth motion track and the ninth motion track;

The first electronic device acquires the tenth motion trajectory from the cloud server;

The first electronic device performs similarity matching on the fourth motion trajectory with the third motion trajectory and the tenth motion trajectory respectively, and determines the similarity between the fourth motion trajectory and the third motion trajectory The matching is successful; and, based on the third motion trajectory whose similarity is successfully matched, correct the fourth motion trajectory, and display the corrected fourth motion trajectory.
The method according to claim 11, wherein the similarity between the first motion trajectory and the second motion trajectory is greater than or equal to a similarity threshold.
The method of claim 11, wherein:

The first electronic device receives a user's instruction, and in response to the user's instruction, acquires the third motion trajectory from the cloud server.
The method of claim 11, wherein:

The cloud server sends indication information to the first electronic device, which is used to instruct the first electronic device to download the third motion trajectory from the cloud server.
The method according to claim 11, wherein the first electronic device is a mobile phone, and the second electronic device is a smart watch.
The method according to claim 11, wherein a sports health application is installed on the first electronic device and the second electronic device respectively.
The method of claim 18, wherein:

The first electronic device displays the fourth motion trajectory after deviation correction on the application interface of the sports health application.
The method of claim 11, wherein the first electronic device and the second electronic device have the same user account.