A method, apparatus, device, and medium for determining motion distance.

Abstract

This application discloses a method, apparatus, device, and medium for determining movement distance, belonging to the field of smart trail technology. The method includes: when a target terminal recognizes a user's face, obtaining the target recognition time of the terminal's face recognition, and querying the user's movement data closest to the target recognition time to obtain filtering data; determining the face recognition terminal corresponding to the filtering data to obtain the filtering terminal, and determining the filtering recognition time of the filtering terminal's face recognition; forming a terminal sequence from the target terminal, the filtering terminal, and the terminals between these two terminals, and determining the maximum and minimum time required for the user to traverse the terminal sequence; if the target recognition time is within a preset range, determining the user's movement distance on the smart trail based on the target terminal's face recognition data. This method allows users to more accurately know their movement distance on the smart trail.

Description

Technical Field

[0001] This invention relates to the field of intelligent walking trail technology, and in particular to a method, apparatus, device, and medium for determining movement distance. Background Technology

[0002] Smart trails, combining leisure and fitness with ease of walking, are gradually becoming a popular fitness activity. Currently, the distance a user travels on a smart trail is typically determined by facial recognition terminals installed along the trail.

[0003] Specifically, multiple facial recognition terminals are typically installed along the walking track of smart trails. When determining a user's distance traveled on the smart trail using these terminals, a method of position accumulation is usually used. That is, if facial recognition terminal A on the smart trail recognizes a user's face, X meters are added to the user's distance traveled; if facial recognition terminal B recognizes the user's face, another X meters are added, and so on. The user's distance traveled is ultimately determined by the number of times the facial recognition terminals on the smart trail recognize the user's face. However, if a facial recognition terminal on the smart trail fails to recognize a user's face, the distance traveled by that user in that area is not accumulated. This results in the user missing a portion of the user's distance traveled, making it impossible for the user to accurately know their distance traveled on the smart trail. Currently, there is no effective solution to this technical problem.

[0004] Therefore, enabling users to more accurately know their movement distance on smart trails is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method, apparatus, device, and medium for determining movement distance, so that users can more accurately know their movement distance on a smart trail. The specific solution is as follows:

[0006] A method for determining the distance traveled includes:

[0007] When the target terminal recognizes the user's face, the time when the target terminal recognizes the user's face is obtained to obtain the target recognition time, and the user's motion data closest to the target recognition time is queried to obtain filtered data; wherein, the target terminal is any face recognition terminal on the smart trail;

[0008] Identify the face recognition terminal corresponding to the filtering data to obtain the filtering terminal, and determine the time when the filtering terminal recognizes the user's face to obtain the filtering recognition time;

[0009] The target terminal, the filtering terminal, and the terminals between the target terminal and the filtering terminal are combined into a terminal sequence, and the maximum and minimum time required for the user to pass through the terminal sequence are determined.

[0010] If the target recognition time is within a preset range, the user's movement distance on the smart trail is determined based on the user's facial recognition data from the target terminal; wherein, the lower limit of the preset range is the sum of the screening and recognition time and the minimum duration, and the upper limit of the preset range is the sum of the screening and recognition time and the maximum duration.

[0011] Preferably, a method for determining the movement distance further includes:

[0012] If the sum of the screening and recognition time and the minimum duration is less than the target recognition time, it is determined that the target terminal has an abnormality in the user's face recognition data.

[0013] Preferably, a method for determining the movement distance further includes:

[0014] The target terminal deletes the user's facial recognition data.

[0015] Preferably, a method for determining the movement distance further includes:

[0016] If the sum of the screening and recognition time and the maximum duration is greater than the target recognition time, it is determined that the user has ended their exercise on the smart trail, and the target terminal stores the user's facial recognition data.

[0017] Preferably, the process of determining the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal includes:

[0018] If the smart trail has only one entrance, then that entrance will be designated as the first entrance;

[0019] The first entrance is determined as the entrance for the user to enter the smart trail, and the user's movement distance on the smart trail is determined based on the facial recognition data of the user by the target terminal.

[0020] Preferably, the process of determining the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal includes:

[0021] If the smart trail has two or more entrances, the entrance closest to the target terminal will be identified as the second entrance;

[0022] The second entrance is determined as the entrance for the user to enter the smart trail, and the user's movement distance on the smart trail is determined based on the facial recognition data of the user by the target terminal.

[0023] Preferably, the process of assembling the target terminal, the filtering terminal, and the terminals between the target terminal and the filtering terminal into a terminal sequence includes:

[0024] Set a corresponding device code for each face recognition terminal on the smart trail;

[0025] If the user moves in the order of the device codes of the face recognition terminals, the terminal sequence is formed by taking the screening terminal and the target terminal as the start and end points, respectively, and including the screening terminal, the target terminal, and the terminals between the screening terminal and the target terminal.

[0026] Accordingly, the present invention also discloses a device for determining movement distance, including a data filtering module, a terminal filtering module, a duration determination module, and a distance determination module;

[0027] The data filtering module is used to obtain the time when the target terminal recognizes the user's face, to obtain the target recognition time, and to query the user's motion data closest to the target recognition time to obtain filtered data; wherein, the target terminal is any face recognition terminal on the smart trail;

[0028] The terminal filtering module is used to determine the face recognition terminal corresponding to the filtering data, obtain the filtering terminal, and determine the time when the filtering terminal recognizes the user's face, obtain the filtering recognition time.

[0029] The duration determination module is used to form a terminal sequence from the target terminal, the filtering terminal, and the terminals between the target terminal and the filtering terminal, and to determine the maximum and minimum duration required for the user to pass through the terminal sequence.

[0030] The distance determination module is used to determine the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal if the target recognition time is within a preset range; wherein, the lower limit of the preset range is the sum of the screening recognition time and the minimum duration, and the upper limit of the preset range is the sum of the screening recognition time and the maximum duration.

[0031] Accordingly, the present invention also discloses a device for determining motion distance, including a memory and a processor;

[0032] The memory is used to store computer programs;

[0033] When the processor executes the computer program, it implements the steps of a method for determining a movement distance as disclosed above.

[0034] Accordingly, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a method for determining a motion distance as disclosed above.

[0035] As can be seen, in this invention, when the target terminal recognizes the user's face, the first step is to obtain the time when the target terminal recognizes the user's face, thus obtaining the target recognition time. Then, the motion data of the user closest to the target recognition time is queried to obtain filtering data. Next, the face recognition terminal corresponding to the filtering data is determined, thus obtaining the filtering terminal. The time when the filtering terminal recognizes the user's face is then determined, thus obtaining the filtering recognition time. Afterward, the target terminal, the filtering terminal, and the terminals between the target terminal and the filtering terminal form a terminal sequence, and the maximum and minimum time required for the user to pass through the terminal sequence are determined. If the target recognition time is within a preset range, the user's movement distance on the smart trail is determined based on the target terminal's face recognition data. The lower limit of the preset range is the sum of the filtering recognition time and the minimum time, and the upper limit of the preset range is the sum of the filtering recognition time and the maximum time. Compared to existing technologies, this method effectively limits the time range for the target terminal to recognize the user's face. Only when the target terminal's face recognition time meets the preset range will the user's movement distance on the smart trail be calculated based on the face recognition data. This effectively reduces the probability of missing user movement data when calculating the user's movement distance. Therefore, this method allows users to more accurately know their movement distance on the smart trail. Correspondingly, the movement distance determination device, equipment, and medium provided by this invention also have the above-mentioned beneficial effects. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0037] Figure 1 A flowchart illustrating a method for determining motion distance provided in an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of an intelligent walkway provided in an embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of another smart trail provided in an embodiment of the present invention;

[0040] Figure 4 This is a structural diagram of a motion distance determination device provided in an embodiment of the present invention;

[0041] Figure 5 This is a structural diagram of a motion distance determination device provided in an embodiment of the present invention. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Please see Figure 1 , Figure 1 A flowchart of a method for determining motion distance provided in an embodiment of the present invention, the method comprising:

[0044] Step S11: When the target terminal recognizes the user's face, the time when the target terminal recognizes the user's face is obtained to get the target recognition time, and the user's motion data closest to the target recognition time is queried to obtain the filtered data; where the target terminal is any face recognition terminal on the smart trail.

[0045] Step S12: Determine the face recognition terminal corresponding to the filtering data, obtain the filtering terminal, and determine the time for the filtering terminal to recognize the user's face, thus obtaining the filtering recognition time;

[0046] Step S13: Form a terminal sequence by combining the target terminal, the filtered terminal, and the terminals between the target terminal and the filtered terminal, and determine the maximum and minimum time required for the user to pass through the terminal sequence;

[0047] Step S14: If the target recognition time is within the preset range, the user's movement distance on the smart trail is determined based on the user's face recognition data from the target terminal; wherein, the lower limit of the preset range is the sum of the screening recognition time and the minimum duration, and the upper limit of the preset range is the sum of the screening recognition time and the maximum duration.

[0048] This embodiment provides a method for determining movement distance, which allows users to more accurately know their movement distance on the smart trail. The method is specifically described using a server as the executing entity.

[0049] In practical applications, smart trails typically have multiple facial recognition terminals. Each terminal identifies a user's face and uploads the information to a server. The server then integrates this information and calculates the user's distance traveled on the smart trail. Furthermore, to more accurately assess and predict user activity, information such as age, height, weight, nickname, photo, and health status can be pre-stored on the server.

[0050] Specifically, when the target terminal recognizes a user's face, it indicates that the target terminal has successfully recognized the user's face image. At this time, the target terminal will upload the time of the face recognition to the server. The target terminal refers to any face recognition terminal on the smart trail. It should be noted that in practical applications, if the target terminal captures the target user's face image but fails to recognize the user's face, the target terminal will upload the user's face image to the server for recognition and screening. If the server successfully screens and recognizes the user's face image, it will send the user's face image to the target terminal, which will then continue to acquire the user's face recognition data. If the server does not find the user's face image in its own repository, it will add the user's face image to its repository and send it to the target terminal, which will then continue to acquire the user's face recognition data.

[0051] When the server receives the target recognition time from the target terminal for facial recognition of a user, it queries the user's motion data closest to that time to obtain filtered data. This is because each facial recognition terminal on the smart trail uploads its facial recognition data to the server when it recognizes a user's face. Therefore, upon receiving the target recognition time, the server can filter out the user's motion data closest to the target recognition time and determine the facial recognition terminal corresponding to the uploaded motion data closest to the target recognition time, thus obtaining the filtered terminals. Once the server has determined the filtered terminals, it determines the time when those terminals performed facial recognition on the user, obtaining the filtered recognition time.

[0052] Next, the server will assemble the target terminal, the filtered terminals, and the terminals between the target terminal and the filtered terminal into a terminal sequence, and determine the maximum and minimum time required for the user to pass through the terminal sequence. It's understandable that when a user passes two adjacent facial recognition terminals on the smart trail, there will be a corresponding minimum and maximum time. Therefore, after assembling the target terminal, the filtered terminals, and the terminals between the target terminal and the filtered terminal into a terminal sequence, the server can determine the maximum and minimum time required for the user to pass through the terminal sequence.

[0053] In this embodiment, to effectively avoid situations where the facial recognition terminal on the smart trail misses capturing the user's movement distance, the target recognition time for the target terminal to recognize the user's face is limited when calculating the user's movement distance on the smart trail. That is, the server will only calculate the user's movement distance on the smart trail based on the facial recognition data from the target terminal if the target recognition time for the target terminal to recognize the user's face meets a preset range. The lower limit of the preset range is the sum of the filtering recognition time and the minimum duration, and the upper limit is the sum of the filtering recognition time and the maximum duration.

[0054] When the target recognition time is within a preset range, it indicates that the user's movement trajectory on the smart trail is normal. At this point, the server can calculate the user's movement distance on the smart trail based on the facial recognition data identified by the target terminal. Obviously, this method can effectively reduce the probability of missing user movement data when calculating the user's movement distance, thus enabling users to more accurately know their movement distance on the smart trail.

[0055] It should be noted that the facial recognition data of the target terminal for the user includes: the recognition area of ​​the target terminal on the smart trail, the time of facial recognition by the target terminal, etc. Furthermore, to further improve the server's calculation speed of the user's movement distance on the smart trail, information such as the entrance and exit locations of the smart trail, as well as the recognition areas corresponding to the facial recognition terminals set up at the entrance and exit locations, can be pre-stored on the server.

[0056] It's conceivable that when the server determines the user's movement area on the smart trail based on the facial recognition data reported by the target terminal, the server can accurately and reliably determine the user's movement distance on the smart trail based on the entrance location of the smart trail and the time it takes for the target terminal to recognize the user's face. Compared to existing technologies, this method essentially limits the time range for the target terminal to recognize the user's face. Only when the target terminal's facial recognition time meets a preset range will the user's movement distance on the smart trail be calculated based on the facial recognition data. This effectively reduces the probability of missing user movement data when calculating the user's movement distance. Therefore, this method allows users to more accurately know their movement distance on the smart trail.

[0057] As can be seen, in this embodiment, when the target terminal recognizes the user's face, the first step is to obtain the time when the target terminal recognizes the user's face, thus obtaining the target recognition time. Then, the motion data of the user closest to the target recognition time is queried to obtain filtering data. Next, the face recognition terminal corresponding to the filtering data is determined, thus obtaining the filtering terminal. The time when the filtering terminal recognizes the user's face is then determined, thus obtaining the filtering recognition time. Afterward, the target terminal, the filtering terminal, and the terminals between the target terminal and the filtering terminal form a terminal sequence, and the maximum and minimum time required for the user to pass through the terminal sequence are determined. If the target recognition time is within a preset range, the user's movement distance on the smart trail is determined based on the target terminal's face recognition data. The lower limit of the preset range is the sum of the filtering recognition time and the minimum time, and the upper limit of the preset range is the sum of the filtering recognition time and the maximum time. Compared to existing technologies, this method effectively limits the time range for the target terminal to recognize the user's face. Only when the target terminal's face recognition time meets the preset range will the user's movement distance on the smart trail be calculated based on the face recognition data. This effectively reduces the probability of missing user movement data when calculating the user's movement distance. Therefore, this method allows users to more accurately know their movement distance on the smart trail.

[0058] Based on the above embodiments, this embodiment further explains and optimizes the technical solution. As a preferred implementation, the above-mentioned method for determining the movement distance further includes:

[0059] If the sum of the screening and recognition time and the minimum duration is less than the target recognition time, it is determined that the target terminal's facial recognition data of the user is abnormal.

[0060] Understandably, if a user maintains normal movement on the smart trail, the target terminal's facial recognition time will be within a preset range. If the sum of the screening terminal's facial recognition time and the minimum duration is less than the target terminal's facial recognition time, it indicates that the user ran from the screening terminal to the target terminal in a very short time, and the time exceeded the user's physical limits. This suggests an anomaly in the target terminal's facial recognition data. In this case, the server will not calculate the user's distance traveled on the smart trail based on the target terminal's facial recognition data.

[0061] As a preferred embodiment, the above-mentioned method for determining the movement distance further includes:

[0062] Delete the user's facial recognition data from the target terminal.

[0063] When the sum of the filtering recognition time and the minimum duration is less than the target recognition time, it indicates that the target terminal's facial recognition data for the user is abnormal and invalid, having no practical reference value. In this case, to reduce the amount of server storage space occupied by abnormal data, the server can directly delete the target terminal's facial recognition data for the user.

[0064] Alternatively, the method for determining the distance of movement described above may also include:

[0065] If the sum of the screening recognition time and the maximum duration is greater than the target recognition time, it is determined that the user has ended their exercise on the smart trail, and the target terminal stores the user's facial recognition data.

[0066] In this embodiment, if the sum of the screening and recognition time of the screening terminal for recognizing the user's face and the maximum duration is greater than the target recognition time of the target terminal for recognizing the user's face, it indicates that the user has paused, rested, or otherwise not engaged in normal exercise on the smart trail, and it also indicates that the user is not able to burn calories according to the normal exercise process.

[0067] If this happens, it means that the user has finished exercising on the smart trail. In order to ensure that the user can accurately know this situation in the future, the server will also store the user's facial recognition data from the target terminal on the server so that the user can track and trace their exercise on the trail in the future.

[0068] Obviously, the technical solution provided in this embodiment can not only ensure that users can accurately and reliably know their movement distance on the smart trail, but also enable users to have a clearer understanding of their movement on the trail.

[0069] Based on the above embodiments, this embodiment further explains and optimizes the technical solution. As a preferred implementation, the above step: determining the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal, includes:

[0070] If the smart trail has only one entrance, then that entrance will be designated as the first entrance;

[0071] The first entrance is identified as the user's entry point into the smart trail, and the user's movement distance on the smart trail is determined based on the facial recognition data of the user from the target terminal.

[0072] In typical cases, smart trails usually have only one entrance. In this scenario, the server can quickly calculate the user's running distance on the smart trail based on the facial recognition data reported by the target terminal. Because the server can determine the user's initial running position on the smart trail based on the first entrance, and can also accurately determine the user's current running position and running time on the smart trail based on the facial recognition data reported by the target terminal, the server can accurately calculate the user's running distance on the smart trail.

[0073] Alternatively, the above steps: the process of determining the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal, include:

[0074] If the smart trail has two or more entrances, the entrance closest to the target terminal will be identified as the second entrance;

[0075] The second entrance is identified as the user's entry point into the smart trail, and the user's movement distance on the smart trail is determined based on the facial recognition data of the user from the target terminal.

[0076] In practical applications, sometimes two or more entrances are set on the smart trail. In this case, in order for the server to calculate the user's movement distance on the smart trail more accurately, in this embodiment, the entrance on the smart trail that is closest to the target terminal is determined as the second entrance, and the second entrance is determined as the entrance for the user to enter the smart trail.

[0077] Because the facial recognition terminals on smart trails are not usually in an abnormal state for a long time, when the target terminal captures a user's face, the entrance on the smart trail closest to the target terminal can be determined as the user's entrance to the smart trail.

[0078] Once the server determines that the user entered the smart trail from the second entrance and started exercising, the server can determine the user's initial running position on the smart trail based on the second entrance. Furthermore, based on the user's facial recognition data reported by the target terminal, the server can determine the user's current running position on the smart trail and the duration of the user's exercise on the smart trail. At this point, the server can accurately calculate the distance the user has traveled on the smart trail.

[0079] Obviously, the technical solution provided in this embodiment can accurately and reliably calculate the user's movement distance on the smart trail.

[0080] Based on the above embodiments, this embodiment further explains and optimizes the technical solution. As a preferred implementation, the above step: the process of forming a terminal sequence from the target terminal, the screening terminal, and the terminals between the target terminal and the screening terminal, includes:

[0081] Set a corresponding device code for each facial recognition terminal on the smart trail;

[0082] If the user moves in ascending order of the device codes of the face recognition terminals, and the device code of the target terminal is greater than the device code of the screening terminal, then the screening terminal and the target terminal are taken as the start and end points respectively, and the screening terminal, the target terminal, and the terminals between the screening terminal and the target terminal are combined to form a terminal sequence.

[0083] In this embodiment, to accurately determine how many face recognition terminals a user passes through on the smart trail from the screening terminal to the target terminal, a corresponding device code is pre-set for each face recognition terminal on the smart trail. This allows the server to more accurately distinguish and identify the face recognition data reported by each face recognition terminal on the smart trail when it receives the data.

[0084] If the user moves in ascending order of the facial recognition terminals, and the device code of the target terminal is greater than that of the screening terminal, it means that the user did not pass through the exit of the smart trail while moving on the trail. In this case, the screening terminal can be used as the starting point, the target terminal as the end point, and the screening terminal, the target terminal, and the terminals between the screening terminal and the target terminal can be used to form a terminal sequence.

[0085] Please see Figure 2 , Figure 2 This is a schematic diagram of a smart walkway provided in an embodiment of the present invention. Figure 2 The smart trail shown has eight facial recognition terminals, designated A, B, C, D, E, F, G, and H. Assuming terminal A is the entrance to the smart trail, terminal H is the exit, the target terminal's device code is F, and the filtering terminal's device code is B, since the target terminal's device code F is greater than the filtering terminal's device code B, the server can directly assemble the filtering terminal B, the target terminal F, and the facial recognition terminals C, D, and E between filtering terminal B and target terminal F into a terminal sequence. That is, the terminal sequence is facial recognition terminals B, C, D, E, and F.

[0086] In practical applications, if a user moves in ascending order of the facial recognition terminals, and the device code of the target terminal is less than that of the screening terminal, it indicates that the user has passed the exit of the smart trail while moving on the trail. In this case, the server can also use the screening terminal as the starting point and the target terminal as the ending point, forming a terminal sequence from the screening terminal, the target terminal, and the terminals between the screening terminal and the target terminal.

[0087] Please see Figure 2 At this point, let's assume that face recognition terminal A is the entrance to the smart trail, face recognition terminal H is the exit of the smart trail, the device code corresponding to the target terminal is B, and the device code corresponding to the screening terminal is G. Since the device code B of the target terminal is less than the device code G of the screening terminal, the server can form a terminal sequence from the screening terminal G, the target terminal B, and the face recognition terminals H and A between the screening terminal G and the target terminal B. That is, the terminal sequence is face recognition terminals G, H, A, B.

[0088] Obviously, the technical solution provided in this embodiment can accurately determine the user's movement on the smart trail.

[0089] To enable those skilled in the art to better understand the implementation principle of the technical solution provided in this application, the method for determining the motion distance provided in this application is described in detail here through an application scenario embodiment.

[0090] Please see Figure 3 , Figure 3 This is a schematic diagram of another smart walkway provided in an embodiment of the present invention. Figure 3 The smart trail shown has six facial recognition terminals, designated as terminals 1, 2, 3, 4, 5, and 6. Terminals 1 and 2 correspond to entrances 1 and 2 of the smart trail, respectively, while terminal 6 corresponds to the exit.

[0091] Assume the distance between face recognition terminal 1 and face recognition terminal 2 is X1, the distance between face recognition terminal 2 and face recognition terminal 3 is X2, the distance between face recognition terminal 3 and face recognition terminal 4 is X3, the distance between face recognition terminal 4 and face recognition terminal 5 is X4, and the distance between face recognition terminal 5 and face recognition terminal 6 is X5. The minimum and maximum duration of the user's journey from face recognition terminal 1 to face recognition terminal 2 are Tmin1 and Tmax1, respectively; the minimum and maximum duration of the user's journey from face recognition terminal 2 to face recognition terminal 3 are Tmin2 and Tmax2, respectively; the minimum and maximum duration of the user's journey from face recognition terminal 3 to face recognition terminal 4 are Tmin3 and Tmax3, respectively; the minimum and maximum duration of the user's journey from face recognition terminal 4 to face recognition terminal 5 are Tmin4 and Tmax4, respectively; and the minimum and maximum duration of the user's journey from face recognition terminal 5 to face recognition terminal 6 are Tmin5 and Tmax5, respectively.

[0092] When face recognition terminal 4 recognizes a user's face, it reports the face recognition time T0 and the face recognition data to the server. The server compares these data to determine that the user entered the smart trail from the entrance corresponding to face recognition terminal 2. Therefore, the user's initial movement distance on the smart trail is d0 = X2 + X3. When the server receives the face recognition time T1 reported by face recognition terminal 4, it queries the user's movement data closest to the time T1 reported by face recognition terminal 4, obtains filtered data, and identifies the face recognition terminal corresponding to the filtered data.

[0093] If the face recognition terminal corresponding to the filtered data is face recognition terminal 3, it means that when the user was exercising on the smart trail, they did not pass through the exit of the smart trail. After entering the track from the entrance, the user only passed through face recognition terminals 3 and 4 on the smart trail. Assume that the face recognition time for face recognition terminal 3 to recognize the user's face is T0, and the minimum and maximum time from face recognition terminal 3 to face recognition terminal 4 are Tmin3 and Tmax3, respectively. If T0 + Tmin3 ≤ T1 ≤ T0 + Tmax3, it means that the facial recognition terminal did not miss capturing the user's face while the user was exercising on the smart trail, and the user's movement trajectory on the smart trail is normal. In this case, the server can calculate the user's movement distance on the smart trail as D = X2 + X3 based on the facial recognition data reported by facial recognition terminal 4. If T1 ≤ T0 + Tmin3, it means that the facial recognition data of the user by facial recognition terminal 4 is abnormal. In this case, the facial recognition data reported by facial recognition terminal 4 can be deleted directly. If T1 ≥ T0 + Tmax3, it means that the user has finished exercising on the smart trail. The user rested or paused during the smart trail, or other situations occurred. In this case, the user's movement distance on the smart trail is D = X2 + X3. However, the user cannot consume their energy according to the normal calorie consumption. In this case, it is only necessary to record the facial recognition data reported by facial recognition terminal 4.

[0094] If the face recognition terminal corresponding to the filtered data is face recognition terminal 5, it means that the user passed the exit of the smart trail while exercising on the smart trail. After entering the smart trail from the entrance corresponding to face recognition terminal 2, the user ran past face recognition terminals 3, 4, 5, 6, and 1, and then passed through face recognition terminals 2 and 3 again. Assume that the face recognition time for face recognition terminal 3 to recognize the user's face is T0. Since the minimum and maximum time for the user to move from face recognition terminal 5 to face recognition terminal 4 are Tmin = Tmin5 + Tmin6 + Tmin1 + Tmin2 + Tmin3 and Tmax = Tmax5 + Tmax6 + Tmax1 + Tmax2 + Tmax3, respectively. If T0+Tmin≤T1≤T0+Tmax, it means the user's movement trajectory on the smart trail is normal. In this case, the server can calculate the user's movement distance D = X2+X3+X4+X5+X6+X1+X2+X3 based on the facial recognition data reported by facial recognition terminal 4. If T1≤T0+Tmin, it means the facial recognition data of the user by facial recognition terminal 4 is abnormal. In this case, the facial recognition data reported by facial recognition terminal 4 can be deleted directly. If T1≥T0+Tmax, it means the user has finished exercising on the smart trail. The user may have rested or paused during the journey. In this case, the user's movement distance on the smart trail is X2+X3+X4+X5+X6+X1+X2+X3. However, the user cannot expend energy according to the normal calorie consumption. In this case, it is only necessary to record the facial recognition data reported by facial recognition terminal 4.

[0095] Obviously, the technical solution provided in this embodiment can accurately determine the user's movement distance on the smart trail.

[0096] Please see Figure 4 , Figure 4 This is a structural diagram of a motion distance determination device provided in an embodiment of the present invention. The device includes a data filtering module 21, a terminal filtering module 22, a duration determination module 23, and a distance determination module 24.

[0097] The data filtering module 21 is used to obtain the time when the target terminal recognizes the user's face, to obtain the target recognition time, and to query the user's motion data closest to the target recognition time to obtain the filtered data; wherein, the target terminal is any face recognition terminal on the smart trail.

[0098] The terminal filtering module 22 is used to determine the face recognition terminal corresponding to the filtering data, obtain the filtering terminal, and determine the time when the filtering terminal recognizes the user's face, thereby obtaining the filtering recognition time.

[0099] The duration determination module 23 is used to form a terminal sequence from the target terminal, the filtered terminal, and the terminals between the target terminal and the filtered terminal, and to determine the maximum and minimum duration required for the user to pass through the terminal sequence.

[0100] The distance determination module 24 is used to determine the user's movement distance on the smart trail based on the user's face recognition data from the target terminal if the target recognition time is within a preset range; wherein, the lower limit of the preset range is the sum of the screening recognition time and the minimum duration, and the upper limit of the preset range is the sum of the screening recognition time and the maximum duration.

[0101] Preferably, a device for determining the movement distance further includes:

[0102] The data determination module is used to determine that the target terminal's facial recognition data of the user is abnormal if the sum of the filtering recognition time and the minimum duration is less than the target recognition time.

[0103] Preferably, a device for determining the movement distance further includes:

[0104] The data deletion module is used to delete the facial recognition data of the user from the target terminal.

[0105] Preferably, a device for determining the movement distance further includes:

[0106] The data storage module is used to determine that the user has finished exercising on the smart trail if the sum of the screening recognition time and the maximum duration is greater than the target recognition time, and to store the facial recognition data of the user by the target terminal.

[0107] Preferably, the distance determination module 24 includes:

[0108] The first determination unit is used to determine the entrance as the first entrance if the smart trail has only one entrance.

[0109] The first determining unit is used to determine the first entrance as the entrance for the user to enter the smart trail, and to determine the user's movement distance on the smart trail based on the facial recognition data of the user by the target terminal.

[0110] Preferably, the distance determination module 24 includes:

[0111] The second determination unit is used to determine the entrance closest to the target terminal as the second entrance if the smart trail has two or more entrances.

[0112] The second determining unit is used to determine the second entrance as the entrance for the user to enter the smart trail, and to determine the user's movement distance on the smart trail based on the facial recognition data of the user by the target terminal.

[0113] Preferably, the duration determination module 23 includes:

[0114] The coding setting unit is used to set a corresponding device code for each face recognition terminal on the smart trail;

[0115] The sequence determination unit is configured to, if the user moves in an order that sequentially increases according to the device codes of the face recognition terminal, take the filtering terminal and the target terminal as the start and end points respectively, and form the terminal sequence by including the filtering terminal, the target terminal, and the terminals between the filtering terminal and the target terminal.

[0116] This invention also discloses a device for determining movement distance, which has the beneficial effects of the aforementioned method for determining movement distance.

[0117] Please see Figure 5 , Figure 5 This is a structural diagram of a motion distance determination device provided in an embodiment of the present invention. The device includes a memory 31 and a processor 32.

[0118] Memory 31 is used to store computer programs;

[0119] The processor 32 is used to implement the steps of a method for determining a motion distance as disclosed above when executing a computer program.

[0120] This invention also discloses a device for determining motion distance, which has the beneficial effects of the aforementioned method for determining motion distance.

[0121] Accordingly, embodiments of the present invention also disclose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a method for determining a motion distance as disclosed above.

[0122] The present invention also discloses a computer-readable storage medium that has the beneficial effects of the aforementioned method for determining motion distance.

[0123] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0124] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0125] The present invention has provided a detailed description of a method, apparatus, device, and medium for determining motion distance. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for determining the distance traveled, characterized in that, include: When the target terminal recognizes the user's face, the time when the target terminal recognizes the user's face is obtained to obtain the target recognition time, and the user's motion data closest to the target recognition time is queried to obtain filtered data; wherein, the target terminal is any face recognition terminal on the smart trail; Identify the face recognition terminal corresponding to the filtering data to obtain the filtering terminal, and determine the time when the filtering terminal recognizes the user's face to obtain the filtering recognition time; The target terminal, the filtering terminal, and the terminals between the target terminal and the filtering terminal are combined into a terminal sequence, and the maximum and minimum time required for the user to pass through the terminal sequence are determined. If the target recognition time is within a preset range, the user's movement distance on the smart trail is determined based on the user's facial recognition data from the target terminal; wherein, the lower limit of the preset range is the sum of the screening and recognition time and the minimum duration, and the upper limit of the preset range is the sum of the screening and recognition time and the maximum duration.

2. The determination method according to claim 1, characterized in that, Also includes: If the sum of the screening and recognition time and the minimum duration is less than the target recognition time, it is determined that the target terminal has an abnormality in the user's face recognition data.

3. The determination method according to claim 2, characterized in that, Also includes: The target terminal deletes the user's facial recognition data.

4. The determination method according to claim 1, characterized in that, Also includes: If the sum of the screening and recognition time and the maximum duration is greater than the target recognition time, it is determined that the user has ended their exercise on the smart trail, and the target terminal stores the user's facial recognition data.

5. The determination method according to claim 1, characterized in that, The process of determining the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal includes: If the smart trail has only one entrance, then that entrance will be designated as the first entrance; The first entrance is determined as the entrance for the user to enter the smart trail, and the user's movement distance on the smart trail is determined based on the facial recognition data of the user by the target terminal.

6. The determination method according to claim 1, characterized in that, The process of determining the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal includes: If the smart trail has two or more entrances, the entrance closest to the target terminal will be identified as the second entrance; The second entrance is determined as the entrance for the user to enter the smart trail, and the user's movement distance on the smart trail is determined based on the facial recognition data of the user by the target terminal.

7. The determining method according to any one of claims 1 to 6, characterized in that, The process of assembling the target terminal, the filtered terminal, and the terminals between the target terminal and the filtered terminal into a terminal sequence includes: Set a corresponding device code for each face recognition terminal on the smart trail; If the user moves in the order of the device codes of the face recognition terminals, the terminal sequence is formed by taking the screening terminal and the target terminal as the start and end points, respectively, and including the screening terminal, the target terminal, and the terminals between the screening terminal and the target terminal.

8. A device for determining the distance of movement, characterized in that, include: The data filtering module is used to obtain the time when the target terminal recognizes the user's face, to obtain the target recognition time, and to query the user's motion data closest to the target recognition time to obtain filtered data; wherein, the target terminal is any face recognition terminal on the smart trail; The terminal filtering module is used to determine the face recognition terminal corresponding to the filtering data, obtain the filtering terminal, and determine the time when the filtering terminal recognizes the user's face, thereby obtaining the filtering recognition time. The duration determination module is used to form a terminal sequence from the target terminal, the filtering terminal, and the terminals between the target terminal and the filtering terminal, and to determine the maximum and minimum duration required for the user to pass through the terminal sequence. A distance determination module is used to determine the user's movement distance on the smart trail based on the user's facial recognition data from the target terminal if the target recognition time is within a preset range; wherein the lower limit of the preset range is the sum of the screening recognition time and the minimum duration, and the upper limit of the preset range is the sum of the screening recognition time and the maximum duration.

9. A device for determining movement distance, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of a method for determining a movement distance as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of a method for determining a movement distance as described in any one of claims 1 to 7.

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