CN116935270A

CN116935270A - Auxiliary management method for user video, storage medium and electronic device

Info

Publication number: CN116935270A
Application number: CN202310769079.3A
Authority: CN
Inventors: 刘玉凤
Original assignee: Qingdao Haier Technology Co Ltd; Haier Smart Home Co Ltd; Haier Uplus Intelligent Technology Beijing Co Ltd
Current assignee: Qingdao Haier Technology Co Ltd; Haier Smart Home Co Ltd; Haier Uplus Intelligent Technology Beijing Co Ltd
Priority date: 2023-06-27
Filing date: 2023-06-27
Publication date: 2023-10-24

Abstract

The application discloses a user video auxiliary management method, a storage medium and an electronic device, and relates to the technical field of intelligent home, wherein the user video auxiliary management method comprises the following steps: acquiring a user video aiming at a target exercise course; the target exercise course comprises at least one course standard action; based on each course standard action in the target exercise course, identifying whether exercise action deviation aiming at the first course standard action exists in the user video; when the deviation of the body-building action is recognized, determining a target body-building instruction material matched with the standard action of the first course based on the body-building material management library; the fitness material management library contains a plurality of fitness standard actions and corresponding fitness instruction materials. Therefore, the deviation action of the user in the exercise course is intelligently identified, the exercise guidance materials matched with the deviation action are automatically provided, and objective evaluation and targeted guidance on the exercise condition of the user in the exercise course are realized.

Description

Auxiliary management method for user video, storage medium and electronic device

Technical Field

The present application relates to the field of internet technologies, and in particular, to a user video auxiliary management method, a storage medium, and an electronic device.

Background

Along with the continuous improvement of the life rhythm and the material level, the requirements of people on healthy life are also continuously improved, and modern body-building courses are novel exercise forms capable of effectively enhancing the physique of users, so that huge user group support is obtained at present, and the modern body-building courses are popular gradually.

However, the current exercise course management mode is also relatively backward, and is generally realized based on the exercise course data of manual and paper edition, so that an exercise training person or a user is often required to fill in the exercise training device, and the exercise training device has the problems of difficult retrospective inquiry, space occupation, easy loss and the like. After the exercise user participates in completing the exercise course, the exercise user cannot review the action points in the exercise course, so that the user is easy to forget after the exercise course. In addition, the professional level of the body-building class coaches in the current industry is uneven, and some coaches cannot provide professional and objective guiding advice, so that the user is difficult to optimize the physical defect of the user, and the body-building class experience of the user is seriously affected.

In view of the above problems, currently, no preferred technical solution is proposed.

Disclosure of Invention

The application provides a user video auxiliary management method, a storage medium and an electronic device, which are used for solving the defects that the key points of exercise actions cannot be reviewed and objective and targeted exercise guidance suggestions cannot be provided in the prior art, and realizing auxiliary management of user course exercise.

The application provides a user video auxiliary management method, which comprises the following steps: acquiring a user video aiming at a target exercise course; the target exercise course includes at least one course standard action; based on each course standard action in the target exercise course, identifying whether exercise action deviation aiming at a first course standard action exists in the user video; when the deviation of the body-building action is identified, determining a target body-building instruction material matched with the standard action of the first course based on a body-building material management library; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

According to the user video auxiliary management method provided by the application, before the user video aiming at the target exercise course is acquired, the method further comprises the following steps: acquiring a user constitution data set; the user constitution data set comprises a plurality of user constitution data corresponding to different constitution measuring time respectively; at least one recommended workout is determined based on the user fitness dataset, wherein the target workout is determined from the at least one recommended workout.

According to the user video auxiliary management method provided by the application, each user constitution data comprises a plurality of user constitution parameters corresponding to different types respectively, wherein after a user constitution data set is acquired, the method further comprises the steps of: determining corresponding user physique indexes based on the user physique parameters and corresponding calculation weights in the user physique data set aiming at the user physique data; the user physical parameters include any one or more of the following: body weight, muscle content, and body fat rate; determining a user constitution change trend based on user constitution indexes corresponding to all user constitution data in the user constitution data set; and generating at least one user fitness suggestion according to the user physical constitution change trend.

According to the method for user video auxiliary management provided by the application, the determining of the corresponding user physique index based on the user physique parameters and the corresponding calculation weights in the user physique data sets comprises the following steps: acquiring weight adjustment information; according to the weight adjustment information, adjusting the calculated weight corresponding to each user physique parameter; for each user physique data in the user physique data set, a corresponding user physique index is determined based on each of the user physique parameters in the user physique data and a corresponding adjusted calculated weight.

According to the user video auxiliary management method provided by the application, the target exercise course comprises an exercise live video course, and the user video comprises a user exercise video collected in real time, wherein the identifying whether exercise action deviation aiming at a first course standard action exists in the user video based on each course standard action in the target exercise course comprises the following steps: acquiring a first course standard action of the fitness live video course corresponding to a first course moment; and when the live time of the course reaches the first course moment, determining a real-time body-building action of the user based on the real-time collected body-building video of the user, and comparing the first course standard action with the real-time body-building action of the user to determine whether body-building action deviation aiming at the first course standard action exists or not.

According to the user video auxiliary management method provided by the application, the real-time body-building action of the user is determined based on the real-time collected user body-building video, and the method comprises the following steps: acquiring user body-building posture information aiming at the target body-building course; and determining real-time body-building actions of the user based on the body-building posture information of the user and the real-time collected body-building video of the user.

According to the user video auxiliary management method provided by the application, when the deviation of the body-building action is identified, the method further comprises the following steps: determining exercise deviation image information matched with the exercise action deviation based on the user video; and sending the exercise action deviation and the exercise deviation image information, so that a display module displays the exercise action deviation and/or the exercise deviation image information.

The application also provides a user video auxiliary management device, which comprises: the data acquisition unit is used for acquiring a user video aiming at a target exercise course; the exercise course includes at least one course standard action; the action recognition unit is used for recognizing whether exercise action deviation aiming at the first course standard action exists in the user video based on each course standard action in the exercise courses; a material determining unit for determining a target fitness guidance material matched with the first course standard action based on a fitness material management library when the deviation of the fitness action is recognized; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

The application also provides an electronic device comprising a memory in which a computer program is stored and a processor arranged to implement a user video auxiliary management method as described in any of the above by execution of the computer program.

The present application also provides a computer-readable storage medium comprising a stored program, wherein the program when run performs a method of user video auxiliary management as described in any one of the above.

The application also provides a computer program product comprising a computer program which when executed by a processor implements a user video auxiliary management method as described in any one of the above.

According to the user video auxiliary management method, the storage medium and the electronic device, through acquiring the exercise image data of the user reference to the target exercise course, the user video is analyzed based on standard actions of each course in the exercise course, whether action deviation exists or not is identified, and when the deviation of the standard actions of the first course is identified, exercise guidance materials matched with the standard actions are found from an exercise material management library. Therefore, by analyzing the body-building image data of the user reference target body-building course, the deviation action of the user in the body-building course is automatically identified, the body-building material management library pre-storing body-building guiding materials corresponding to various body-building standard actions is utilized, the body-building guiding materials matched with the deviation action can be automatically provided, objective evaluation of the movement condition of the user in the body-building course is realized, the targeted guidance can be provided, the user can take the body-building action key points repeatedly, and the body-building course experience of the user is optimized.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described, and it will be apparent to those skilled in the art that other drawings can be obtained according to these drawings without inventive effort.

FIG. 1 is a schematic diagram of a hardware environment of a user video auxiliary management method according to an embodiment of the present application;

FIG. 2 illustrates a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application;

FIG. 3 illustrates a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application;

FIG. 4 illustrates a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application;

FIG. 5 illustrates a flowchart of one example of a process of identifying exercise action bias in a live curriculum scenario in accordance with an embodiment of the application;

FIG. 6 illustrates a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application;

FIG. 7 illustrates a block diagram of an example of a fitness management information system incorporating a user video assistance management method according to an embodiment of the present application;

FIG. 8 shows a block diagram of an example of a user video auxiliary management apparatus according to an embodiment of the present application;

FIG. 9 shows a block diagram of an example of a user video auxiliary management apparatus according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of an electronic device provided by the present application.

Detailed Description

In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

According to one aspect of the embodiment of the application, a user video auxiliary management method is provided. The user video auxiliary management method is widely applied to full-house intelligent digital control application scenes such as intelligent Home (Smart Home), intelligent Home equipment ecology, intelligent Home (Intelligence House) ecology and the like. Alternatively, in the present embodiment, the above-described user video auxiliary management method may be applied to a hardware environment constituted by the terminal device 102 (or client) and the server 104 (or server) as shown in fig. 1. As shown in fig. 1, the server 104 is connected to the terminal device 102 through a network, and may be used to provide services (such as application services and the like) for a terminal or a client installed on the terminal, a database may be set on the server or independent of the server, for providing data storage services for the server 104, and cloud computing and/or edge computing services may be configured on the server or independent of the server, for providing data computing services for the server 104.

The network may include, but is not limited to, at least one of: wired network, wireless network. The wired network may include, but is not limited to, at least one of: a wide area network, a metropolitan area network, a local area network, and the wireless network may include, but is not limited to, at least one of: WIFI (Wireless Fidelity ), bluetooth. The terminal device 102 may not be limited to a PC, a mobile phone, a tablet computer, an intelligent air conditioner, an intelligent smoke machine, an intelligent refrigerator, an intelligent oven, an intelligent cooking range, an intelligent washing machine, an intelligent water heater, an intelligent washing device, an intelligent dish washer, an intelligent projection device, an intelligent television, an intelligent clothes hanger, an intelligent curtain, an intelligent video, an intelligent socket, an intelligent sound box, an intelligent fresh air device, an intelligent kitchen and toilet device, an intelligent bathroom device, an intelligent sweeping robot, an intelligent window cleaning robot, an intelligent mopping robot, an intelligent air purifying device, an intelligent steam box, an intelligent microwave oven, an intelligent kitchen appliance, an intelligent purifier, an intelligent water dispenser, an intelligent door lock, and the like.

Fig. 2 shows a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application. As to the implementation of the method embodiment of the present application, it may be that server 104 as in fig. 1 is employed to provide the user with an auxiliary management service of the exercise course by processing the user data transmitted by terminal device 102.

As shown in fig. 2, in step S210, a user video for a target workout is acquired.

In some examples of embodiments of the present application, a user may perform exercise by referencing a target exercise session online or on-site in a gym, acquire user videos in real-time using terminal device 102, and upload to server 104 in real-time. Additionally or alternatively, the user may select a target exercise course of interest on the exercise course client, record exercise images of the user while learning the course by using the photographing device, and upload user videos corresponding to the target exercise course to the server 104 through the terminal device 102 after the recording is completed.

It should be appreciated that in some embodiments, the camera device and/or workout client may be integrated into the terminal device 102 as functional modules.

Here, the exercise course includes at least one course standard action, and the exercise course may be composed of individual course standard actions, or the exercise course may further include other actions than the course standard action, such as a preliminary action. In some examples, the definition may be made for each standard action in the workout, such as predefining standard actions in the workout including flat plate support, roll abdomen, squat, etc. In addition, workouts may include a variety of media formats, such as video, live, text, audio, etc., as should not be limiting herein. In some embodiments, the exercise session may be presented as a video, and the corresponding session standard actions may be defined by a set of video frames of a particular play time interval in the video.

In step S220, based on each of the lesson standard actions in the target workout, it is identified whether there is a workout action deviation in the user video for the first lesson standard action.

Here, the exercise motion deviation may include a variety of motion deviation types, such as user not performing a standard motion, user motion not reaching a standard, and so forth. For example, various image recognition techniques, such as neural network models, may be utilized to capture limb movements of a person in a user's video and determine that there are situations in which the user is not performing standard movements when the number of captured workouts is less than the number of standard workout movements in the target workout. Additionally, the captured limb movements may be compared and verified based on the gesture requirement specification related to each course standard movement to determine the standard movement that is not performed, and/or identify whether there is a situation that the user movement does not reach the standard, for example, the gesture requirement specification of the tablet support standard is: the brain bag is not raised, the elbows are vertical to the ground, the head, the buttocks and the ankle are in a straight line, the waist and the back are straight, the abdomen is tightened, and the feet are opened and have the same width as the shoulders.

In step S230, when it is identified that there is a deviation in the exercise activity, a target exercise guidance material that matches the first course standard activity is determined based on an exercise material management library, wherein the exercise material management library contains a plurality of exercise standard activities and corresponding exercise guidance materials. Here, the exercise guide material may be in the form of exercise guide articles, images, and/or videos, the particular presentation of which should not be limited herein. In some examples, the workout materials in the workout materials management library may be determined by merging a plurality of workouts or workout plans, for example, collecting workout video courses and workout articles from a plurality of workouts platforms, and extracting and predefining various types of workout standard actions and corresponding workout materials through machining and finishing.

In one example of an embodiment of the present application, the fitness material management library may be deployed directly in the server 104 to enable guidance of user biased fitness actions. In another example of an embodiment of the present application, the workout materials management library may also be deployed on a third party materials platform, which may be accessed by server 104 through first course standard actions to implement cross-platform invocation of workout guide materials.

According to the embodiment of the application, the user video aiming at the target exercise course is obtained, the standard actions of each course in the target exercise course are utilized to analyze the exercise actions of the user in the user video so as to identify whether exercise action deviation exists, and when the exercise action deviation exists, the exercise material management library is utilized to match corresponding target exercise guidance materials. Therefore, by analyzing the body-building image data of the user reference target body-building course, the irregular actions of the user in the body-building course can be automatically identified, the body-building material management library pre-storing body-building guiding materials corresponding to various body-building standard actions can be utilized, the body-building guiding materials matched with the body-building actions which do not reach the standard can be automatically provided, objective evaluation of the movement condition of the user in the body-building course can be realized, the targeted guidance can be provided, the key points of the user's multi-disc body-building actions are facilitated, the physical quality of the user is targeted enhanced, and the body-building course experience of the user is optimized.

In some examples of embodiments of the application, when a workout deviation is identified, server 104 determines workout image information that matches the workout deviation based on the user video. Further, the server 104 transmits the exercise deviation and the exercise deviation image information such that the display module displays the exercise deviation and the exercise deviation image information. Here, the display module may be disposed on the terminal device 102 or other electronic device. Illustratively, the server 104 transmits the exercise movement deviation and exercise deviation image information to the terminal device 102, such that the terminal device 102 invokes its display module to display the exercise movement deviation and exercise deviation image information. It should be understood that the display module may also be disposed outside the terminal device 102, for example, the terminal device 102 may transmit exercise deviation and exercise deviation image information to the display module for display, which falls within the scope of the embodiments of the present application. Therefore, the body-building user can learn body-building deviation image information when deviation occurs while learning that body-building action deviation exists for corresponding course standard actions, and is helpful for the user to compare and train with target body-building guidance materials according to the body-building deviation image information, the irregular actions of the user are corrected, the user does not need to review the deviation images by himself, and the efficiency of the user for realizing standard body-building can be improved.

Fig. 3 shows a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application. Regarding the implementation of the method embodiment of the present application, the server 104 as shown in fig. 1 may be used to provide the information recommendation service for the exercise course for the user.

As shown in fig. 3, in step S310, a user constitution data set is acquired. Here, the user constitution data set includes a plurality of user constitution data corresponding to different physical measurement times, respectively, for example, user constitution data generated by a user regularly performing physical measurement by a physical measurement device.

Illustratively, in one aspect, the user fitness data may represent one or more fitness parameters, such as body weight, body fat rate, and the like. On the other hand, the user physical data may represent an explanation of the overall physical state of the user, for example, the user physical index determined by comprehensively considering a plurality of user physical parameters may be physical scores or physical ratings.

In step S320, at least one recommended workout is determined based on the user fitness dataset. In some examples, when a user's recent fitness is found to be progressively weaker by analyzing the user's fitness dataset, it is determined that various fitness courses that promote fitness should be recommended for the user. In other examples, when a user's physical data set is analyzed to find that a physical index is not qualified or has a poor trend in the recent past, a workout for enhancing the physical index is recommended to the user, for example, when the recent weight index of the user is continuously increasing, a workout of the aerobic exercise type should be recommended to the user.

According to the embodiment of the application, the user physique data of the user in a period of time are comprehensively considered, and the recommended exercise course is determined according to the user physique data, so that the matching degree of the recommended exercise course and the physique condition of the user can be effectively improved, and the economic transformation of the recommended course can be optimized.

It should be noted that, in some service scenarios, the embodiment described in fig. 2 and the embodiment described in fig. 3 may be coupled. Specifically, the target exercise course is determined according to at least one recommended exercise course, for example, after various exercise courses are recommended to the user through the embodiment as described in fig. 3, the user selects the target exercise course of interest and exercises with reference to the course, thereby realizing recognition of exercise deviation during exercise of the user and pushing the matched exercise guide material through the embodiment as described in fig. 2.

Fig. 4 shows a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application. Regarding the implementation of the method embodiment of the present application, the server 104 as shown in fig. 1 may be used to provide personalized fitness advice for the physical type of the user.

Here, each user physical constitution data includes a plurality of physical constitution parameters respectively corresponding to different types of users, for example, various types of physical constitution parameters collected by one physical measurement. Illustratively, the first and second modules are connected to one another. The user physical parameters include any one or more of the following: body weight, muscle content, and body fat rate. In addition, the user physical parameters may also include other types of parameters not described herein, such as user muscle distribution areas, and the like.

As shown in fig. 4, in step S410, for each user constitution data in the user constitution data set, a corresponding user constitution index is determined based on each user constitution parameter in the user constitution data and a corresponding calculation weight. Here, the user physique data can be used to reflect the physique state of the whole user, and weight calculation is performed on the physique parameters of each user to obtain the physique index of the user. In addition, the user physical index may represent index data that quantizes physical data, such as hierarchical quantization (class a, class B, class C, etc.) or score quantization (100 points, 80 points, etc.).

In the process of calculating the user physical index, the corresponding scores can be respectively matched according to the intervals corresponding to different user physical parameters, and then the quantized user physical index corresponding to the scores can be obtained through weighted calculation.

In step S420, a user physical variation trend is determined based on the user physical index corresponding to each user physical data in the user physical data set. For example, the user constitution change trend graph may be drawn according to the user constitution indexes corresponding to the user constitution data at different time points.

In step S430, at least one user fitness suggestion is generated according to the user' S physical fitness trend. Here, the exercise advice may be advice other than the exercise course, which helps to improve the physical constitution of the user, such as diet adjustment, regular work and rest time, and the like. Illustratively, according to the physical change characteristics of the user, searching and inquiring are carried out on the knowledge question-answer platform to obtain corresponding answers so as to determine the physical fitness suggestion of the user.

In some examples of embodiments of the present application, terminal device 102 receives the user physical fitness trend and user fitness advice from server 104 and displays the user physical fitness trend graph and user fitness advice on terminal device 102.

According to the embodiment of the application, the physique data of the user physique data set at different times are analyzed to obtain the physique change trend of the user, and corresponding user body-building suggestions are provided, so that the specific body-building suggestions can be provided while the physique change trend of the user is expressed, and the high intelligence and scientificity of the auxiliary body-building management of the user are realized.

With respect to the above step S410, it should be understood that the calculation weight corresponding to each user physical parameter can reflect the importance of different types of parameters in the user physical data. Here, on the one hand, scientific and objective, e.g., scientifically verified, user constitution data may be employed. On the other hand, in order to meet the personalized requirements of different users, the users can also adjust according to the own requirements.

In some examples of the embodiments of the present application, the user may perform a personalized operation on the terminal device 102, adjust the calculated weights of the physical parameters of different users, and send the weight adjustment information to the server 104. Then, the server 104 adjusts the calculated weights corresponding to the physical parameters of the respective users according to the weight adjustment information for the terminal device 102. Further, the server 104 determines, for each user physical data in the user physical data set, a corresponding user physical index based on each user physical parameter in the user physical data and the corresponding adjusted calculation weight. Therefore, the calculation weights of different physical parameters are adjusted according to the individual demands of the users, so that the physical indexes of the users are updated according to the demands of the users, and the individual demands of different users are met. For example, the user may increase the calculation weight corresponding to the body fat rate and decrease the calculation weight corresponding to the body weight, so as to trigger the recalculation and update of the physique data of the user, thereby meeting the important attention requirement of the user on the body fat rate.

FIG. 5 illustrates a flowchart of one example of a process for identifying exercise action bias in a live curriculum scenario in accordance with an embodiment of the present application. In an example of an embodiment of the present application, the target workout comprises a live workout video workout, and the user video comprises a live captured user workout video. Regarding the implementation subject of the method embodiment of the present application, it may be that the server 104 as shown in fig. 1 is used to identify and normalize the deviation of the exercise actions of the user in the live exercise video lesson scenario.

As shown in fig. 5, in step 510, a first lesson standard action is obtained for a fitness live video lesson corresponding to a first lesson time. Here, the exercise live video lesson may be a live video lesson for an exercise coach, or may be live by using a recorded video lesson, which should not be limited herein.

In some examples, the first curriculum instant is an instant that does not occur in the current live scene, and the pre-analysis processing of curriculum standard actions involved in the video is implemented by the first curriculum instant.

In step 520, when the live time of the lesson reaches the first lesson time, determining a real-time user exercise based on the real-time acquired user exercise video, and comparing the first lesson standard exercise with the real-time user exercise to determine whether there is an exercise deviation for the first lesson standard exercise. In some business scenarios, a user may access the exercise video live studio and perform exercise with reference to the exercise live video, and the terminal device 102 may upload the user exercise video collected in real time to the server 104, so that the server 104 may compare the character actions in the course with the character actions in the user exercise video in real time, to identify whether there is an exercise action deviation.

In some examples, by adopting image frame character motion recognition and comparison technology, such as openGL model or other machine learning model, real-time image frame analysis is performed on user exercise video and live video courses, whether the user has a problem of nonstandard motion or not is determined, and further, the recognized motion problem and corresponding user exercise picture can be rapidly transmitted to the user in the live broadcast process, for example, notification is performed in a window frame manner in the terminal device 102, so that the user can rapidly learn about exercise motion deviation in the live broadcast process, and rapid correction of exercise motion is facilitated.

With respect to the above-described step S520, in determining the user 'S real-time exercise motion, in addition to using the image recognition technology, the accuracy of the determined user' S real-time exercise motion may be improved by the gesture sensing module in the terminal device 102. For example, terminal device 102 can upload user workout pose information for a target workout to server 104, such that server 104 can determine a user real-time workout motion based on the user workout pose information and the user workout video collected in real-time. Here, the information type of the user's exercise posture information may include angle sensing information, distance sensing information, etc., should not be limited herein, and may be adjusted with different types of course files.

Fig. 6 shows a flowchart of an example of a user video auxiliary management method according to an embodiment of the present application. Regarding the implementation subject of the method embodiment of the present application, the terminal device 102 as shown in fig. 1 may be adopted to implement the auxiliary management service for the exercise course by collecting the exercise image data of the user when the user is on the exercise course and receiving the feedback from the server 104.

In step S610, in response to the detected user operation conforming to the preset first operation condition, a target exercise course corresponding to the user operation is determined, and a user video corresponding to the target exercise course is acquired. The target exercise session includes at least one session standard action, and for further details, reference is made to the description above in connection with other embodiments, which are not repeated here. In addition, the user video can be various image data, such as video or image sets uploaded by real-time collection, or video or image sets recorded by the user for whole courses.

In some examples, terminal device 102 may display multiple workouts, and the user may select a workout of interest by interactive operation to determine a target workout. While the user selects the target exercise session, the terminal device 102 may enable the camera module to capture the user video in the set area. It should be appreciated that in some embodiments, the camera module may also be deployed outside of the terminal device 102, such as the camera module capturing user video and transmitting the captured user video to the terminal device 102.

In step S620, the user video and the target workout are sent to the server, so that the server identifies a deviation of the workout motion for the standard motion of the first workout based on the user video and determines corresponding workout guide material. For specific operations at the server, reference may be made to the description above in connection with the method embodiments of fig. 2-5.

In step S630, the exercise motion bias and the target exercise guidance material are received from the server.

According to the embodiment of the application, a user can collect the body-building image data when the user goes on a body-building course and report the body-building image data through the client, and the user video auxiliary management server is utilized to realize the recognition of deviation actions in the body-building process and provide corresponding body-building guidance materials with objectivity, so that the body-building user can intelligently help to standardize the course body-building actions.

With respect to step S610 described above, in some examples of embodiments of the present application, the client may receive at least one recommended workout from the server, and in turn, the client determines a target workout in response to the detected course selection operation for the at least one recommended workout. Therefore, the method is beneficial to improving the economic benefit of recommended course operation.

With respect to step S630 described above, in some examples of embodiments of the present application, the target fitness instruction material, the fitness action bias, and the fitness bias image information are received from the server. Here, the exercise deviation image information is image information that the service terminal determines to match the exercise movement deviation based on the user video. Further, based on the display module, at least one of the following is displayed: target fitness instruction materials, fitness action deviation and fitness deviation image information. In some examples, the target workout guide material, the workout bias, and the workout bias image information may be displayed simultaneously. Therefore, the body-building user can learn body-building deviation image information when deviation occurs while learning that body-building action deviation exists for corresponding course standard actions, and is helpful for the user to compare and train with target body-building guidance materials according to the body-building deviation image information, the irregular actions of the user are corrected, the user does not need to review the deviation images by himself, and the efficiency of the user for realizing standard body-building can be improved.

In some examples of the embodiment of the application, the user video auxiliary management method as in the embodiment of the application can be implemented in a live course scene. Specifically, the target workout includes a live workout video workout, and the user video includes a user workout video captured in real-time. With regard to the above step S620, based on the gesture sensing module, user exercise gesture information for the target exercise course is collected, and further user exercise gesture information and user exercise video collected in real time are transmitted, so that the service terminal determines real-time exercise actions of the user based on the user exercise gesture information and the user exercise video collected in real time. Thus, the server 104 is facilitated to fuse the multidimensional information to determine the real-time user exercise motion, thereby ensuring high accuracy of the detected real-time user exercise motion.

Fig. 7 shows a block diagram of an example of a fitness management information system integrated with a user video-assisted management method according to an embodiment of the present application. Here, the exercise management information system may be integrated with the terminal device 102 by way of an exercise application that enables user video-assisted management functions for the exercise user through data interaction with the server 104.

As shown in fig. 7, the fitness management information system 700 is a fitness member oriented management system, and specifically includes a course management module 710, a fitness report module 720, a recommendation data module 730, a message management module 740, an opinion feedback module 750, and a personal information module 760. After the user logs in the system through the terminal equipment, the system can carry out course management, can check personal data and constitution reports, can check various message notices, can timely feed back if problems exist, carries out self-adjustment according to the reply information and the guide document, consolidates the key points of the reinforced course, and improves the action accuracy. Through course management module 710, fitness personnel's course inquiry, course appointment, post-class assessment, post-class data can be achieved. The personal information module 760 can realize the management and maintenance of personal information and contract information of the body-building personnel.

Therefore, the management information system omits the work of arranging and storing paper edition body-building data, and the body-building user can check the body-building data, relevant course guidance, personally recommended courses and suggestions at any time, thereby improving the user satisfaction.

Illustratively, online management of user courses is accomplished through course management module 710. Specifically, after the user enters the system, through course management, when the user can find out the rest of the private teaching, if the rest of the private teaching is 0, a reservation entry is provided, and a telephone call or information sending mode can be sent to a coach to conduct the continuation of the private teaching course. In addition, when the private teaching time is not 0, the user can reserve the teaching time to confirm the teaching, and perform self-post-teaching assessment after the teaching, and meanwhile, the coach performs post-teaching text or voice assessment summary according to the teaching condition of the user and issues video files or pictures of the current course of the user. Further, aiming at the key points of the course and the performance of the user, the system intelligently recommends the guide article or the guide video of the course. In addition, the course management module 710 may provide public course management functions, and the user may reserve public courses and confirm the course, and may perform post-course feedback after the course.

Illustratively, in the constitution report module 720, the fitness user can view all the constitution reports of the past history, and can generate a corresponding trend chart according to a certain time dimension, and intelligently recommend guide articles or guide videos and reasonable healthy diet suggestions according to the constitution report trend chart of the user.

Illustratively, in the recommended materials module 730, the recommended guiding materials received by the fitness user are integrated and displayed in a classified manner, which specifically includes: post-class evaluation, post-class guide articles, post-class guide videos, recommendation data of trend graphs, recommendation data of past medical history, recommendation data of living habits and recommendation data of opinion feedback. Therefore, uncertainty of manual guidance is solved, and users can consolidate after class through various online guidance, so that action accuracy is improved.

Illustratively, in the message management module 740, a system message, an activity message, a course alert message, a contract expiration alert message, and course confirmation can be performed through the course alert message.

Illustratively, in the intent feedback module 750, the fitness user may create a question feedback submission to view the system reply message. Historical all opinion feedback may be viewed.

Illustratively, in personal information module 760, the fitness user may view the base material and contract information. Specifically, the basic data includes personal identity information, past medical history and living habit of the user. The contract information shows the contract type, start-stop time, and expiration specification of the user. Therefore, under the condition that the user information authorizes compliance, the system can pertinently conduct personalized recommendation, body-building guide files of various sources aiming at the personalized recommendation of the user are stored online, and the working efficiency and course accuracy are improved.

All the fitness data of the user, including personal information, course information, physique information and the like, can be managed on line through the fitness management information system, and the accuracy and traceability of the data are improved without recording historical body measurement reports and evaluation of the past courses through paper. In addition, aiming at the online data of the body-building user, courses can be intelligently adjusted or recommended in real time, and targeted training is realized. Therefore, intelligent recommendation can be performed aiming at the online data of the user, and the user is attracted to pay more attention to the health condition and the body-building effect of the user. The user does not need to repeatedly find a coach to confirm the action key points after class, and can perform self-action adjustment through online evaluation and online guidance files, so that the action accuracy is improved, the user can manage the user himself better, and the effect of strengthening physique is achieved.

The user video auxiliary management device provided by the application is described below, and the user video auxiliary management device described below and the user video auxiliary management method described above can be referred to correspondingly.

Fig. 8 shows a block diagram of an example of a user video auxiliary management apparatus according to an embodiment of the present application.

As shown in fig. 8, the user video auxiliary management apparatus 800 includes a data acquisition unit 810, an action recognition unit 820, and a material determination unit 830.

A data acquisition unit 810 for acquiring a user video for a target exercise course; the exercise course includes at least one course standard action;

an action recognition unit 820, configured to recognize, based on each course standard action in the exercise course, whether there is an exercise action deviation for the first course standard action in the user video;

a material determining unit 830 that determines a target fitness guidance material matching the first course standard action based on a fitness material management library when it is recognized that the fitness action deviation exists; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

Fig. 9 shows a block diagram of an example of a user video auxiliary management apparatus according to an embodiment of the present application.

As shown in fig. 9, the user video auxiliary management apparatus 900 includes a data acquisition unit 910, a data transmission unit 920, and a material reception unit 930.

A data acquisition unit 910, configured to determine a target exercise course corresponding to a user operation in response to the detected user operation conforming to a preset first operation condition, and acquire a user video corresponding to the target exercise course; the target workout includes at least one workout standard action.

A data sending unit 920, configured to send the user video and the target exercise course to a server, so that the server identifies whether there is an exercise action deviation for a first course standard action in the user video based on each course standard action in the target exercise course, and when it is identified that there is the exercise action deviation, determines a target exercise guidance material matched with the first course standard action based on an exercise material management library; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

And the material receiving unit 930 is configured to receive the exercise deviation and the target exercise guidance material from the server.

Fig. 10 illustrates a physical schematic diagram of an electronic device, as shown in fig. 10, which may include: a processor 1010, a communication interface (Communications Interface) 1020, a memory 1030, and a communication bus 1040, wherein the processor 1010, the communication interface 1020, and the memory 1030 communicate with each other via the communication bus 1040. Processor 1010 may invoke logic instructions in memory 1030 to perform a user video auxiliary management method comprising: acquiring a user video aiming at a target exercise course; the target exercise course includes at least one course standard action; based on each course standard action in the target exercise course, identifying whether exercise action deviation aiming at a first course standard action exists in the user video; when the deviation of the body-building action is identified, determining a target body-building instruction material matched with the standard action of the first course based on a body-building material management library; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

Further, the logic instructions in the memory 1030 described above may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

In another aspect, the present application also provides a computer program product, the computer program product including a computer program, the computer program being storable on a computer readable storage medium, the computer program, when executed by a processor, being capable of executing the user video auxiliary management method provided by the above methods, the method comprising: acquiring a user video aiming at a target exercise course; the target exercise course includes at least one course standard action; based on each course standard action in the target exercise course, identifying whether exercise action deviation aiming at a first course standard action exists in the user video; when the deviation of the body-building action is identified, determining a target body-building instruction material matched with the standard action of the first course based on a body-building material management library; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

In still another aspect, the present application further provides a computer readable storage medium, where the computer readable storage medium includes a stored program, where the program executes a user video auxiliary management method provided by the above methods, and the method includes: acquiring a user video aiming at a target exercise course; the target exercise course includes at least one course standard action; based on each course standard action in the target exercise course, identifying whether exercise action deviation aiming at a first course standard action exists in the user video; when the deviation of the body-building action is identified, determining a target body-building instruction material matched with the standard action of the first course based on a body-building material management library; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. The auxiliary management method for the user video is characterized by being applied to a server, and comprises the following steps:

acquiring a user video aiming at a target exercise course; the target exercise course includes at least one course standard action;

based on each course standard action in the target exercise course, identifying whether exercise action deviation aiming at a first course standard action exists in the user video;

when the deviation of the body-building action is identified, determining a target body-building instruction material matched with the standard action of the first course based on a body-building material management library; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

2. The user video auxiliary management method according to claim 1, wherein before acquiring the user video for the target exercise course, the method further comprises:

acquiring a user constitution data set; the user constitution data set comprises a plurality of user constitution data corresponding to different constitution measuring time respectively;

at least one recommended workout is determined based on the user fitness dataset, wherein the target workout is determined from the at least one recommended workout.

3. The method according to claim 2, wherein each of the user physique data includes a plurality of user physique parameters respectively corresponding to different types, and the user physique parameters include any one or more of the following: body weight, muscle content and body fat rate,

wherein, after acquiring the user constitution data set, the method further comprises:

determining corresponding user physique indexes based on the user physique parameters and corresponding calculation weights in the user physique data set aiming at the user physique data;

determining a user constitution change trend based on user constitution indexes corresponding to all user constitution data in the user constitution data set;

And generating at least one user fitness suggestion according to the user physical constitution change trend.

4. A user video auxiliary management method according to claim 3, wherein the determining, for each user constitution data in the user constitution data set, a corresponding user constitution index based on each of the user constitution parameters in the user constitution data and a corresponding calculation weight comprises:

acquiring weight adjustment information;

according to the weight adjustment information, adjusting the calculated weight corresponding to each user physique parameter;

for each user physique data in the user physique data set, a corresponding user physique index is determined based on each of the user physique parameters in the user physique data and a corresponding adjusted calculated weight.

5. The method of claim 1, wherein the target workout comprises a live workout video workout and the user video comprises a live user workout video,

wherein the identifying whether there is a workout deviation from a first workout standard action in the user video based on each of the curriculum standard actions in the target workout comprises:

Acquiring a first course standard action of the fitness live video course corresponding to a first course moment;

and when the live time of the course reaches the first course moment, determining a real-time body-building action of the user based on the real-time collected body-building video of the user, and comparing the first course standard action with the real-time body-building action of the user to determine whether body-building action deviation aiming at the first course standard action exists or not.

6. The method of claim 5, wherein determining the user real-time exercise based on the real-time acquired user exercise video comprises:

acquiring user body-building posture information aiming at the target body-building course;

and determining real-time body-building actions of the user based on the body-building posture information of the user and the real-time collected body-building video of the user.

7. The user video auxiliary management method according to claim 1, wherein when the deviation of the exercise action is recognized, the method further comprises:

determining exercise deviation image information matched with the exercise action deviation based on the user video;

and sending the exercise action deviation and the exercise deviation image information, so that a display module displays the exercise action deviation and/or the exercise deviation image information.

8. A user video auxiliary management apparatus, comprising:

the data acquisition unit is used for acquiring a user video aiming at a target exercise course; the exercise course includes at least one course standard action;

the action recognition unit is used for recognizing whether exercise action deviation aiming at the first course standard action exists in the user video based on each course standard action in the exercise courses;

a material determining unit for determining a target fitness guidance material matched with the first course standard action based on a fitness material management library when the deviation of the fitness action is recognized; the body-building material management library comprises a plurality of body-building standard actions and corresponding body-building guide materials.

9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program when run performs the method of any one of claims 1 to 7.

10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to any of claims 1 to 7 by means of the computer program.