Method, device and computer-readable storage medium for determining motion prompts

Abstract

The present invention discloses a method, device and computer-readable storage medium for determining a motion prompt, the method comprising: obtaining skin marker points corresponding to an object to be analyzed collected at different times, the skin marker points including color markers and / or light spot markers; determining the strain of the object to be analyzed during the skin marker point collection period according to the skin marker points, and determining the human body three-dimensional structure information corresponding to the object to be analyzed according to the skin marker points, the human body three-dimensional structure information including skeleton and muscle geometry information; determining the muscle group strength of the object to be analyzed according to the strain and the human body three-dimensional structure information; determining the motion prompt content corresponding to the object to be analyzed according to the muscle group strength. The present invention can reduce the limitations of motion prompts.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and device for determining a motion prompt, and a computer-readable storage medium. Background Art

[0002] Due to time and other factors, home fitness has become an option for exercise, but non-professional exercise methods can easily cause physical damage or fail to achieve fitness results; the current method of determining exercise prompts is relatively traditional, and most of them are directly pushing the same exercise prompt content to a group of people. The push content selected by this method has certain limitations and cannot be accurately pushed according to the user's physical condition. Summary of the invention

[0003] The embodiments of the present invention provide a method, an apparatus and a computer-readable storage medium for determining a motion prompt, aiming to solve the technical problem of how to reduce the limitations of the method for determining a motion prompt.

[0004] Acquire skin marking points corresponding to the object to be analyzed collected at different times, wherein the skin marking points include color markings and / or light spot markings;

[0005] Determine the strain of the object to be analyzed within the skin marker point acquisition period according to the skin marker points, and determine the three-dimensional human body structure information corresponding to the object to be analyzed according to the skin marker points, wherein the three-dimensional human body structure information includes geometric information of the skeleton and muscles;

[0006] Determine the muscle strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body;

[0007] The exercise prompt content corresponding to the object to be analyzed is determined according to the muscle group strength.

[0008] In one embodiment, the step of determining the strain of the object to be analyzed within the skin marker point acquisition period according to the skin marker points, and determining the human body three-dimensional structure information corresponding to the object to be analyzed according to the skin marker points includes:

[0009] Inputting the skin marker points into a muscle group strength determination model, wherein the muscle group strength determination model determines the corresponding strain conditions according to the skin marker points, and obtains the three-dimensional structure information of the human body corresponding to the skin marker points;

[0010] The step of determining the muscle strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body comprises:

[0011] The muscle group strength output by the muscle group strength determination model is obtained, wherein the muscle group strength determination model obtains and outputs the corresponding muscle group strength according to the strain condition and the three-dimensional structure information of the human body.

[0012] In one embodiment, before the step of acquiring skin marker points corresponding to the object to be analyzed collected at different times, the method further includes:

[0013] Acquire a training set, wherein the training set includes skin marker point samples and muscle group strength samples;

[0014] Model training is performed on the model to be trained according to the training set to obtain the muscle group strength determination model.

[0015] In one embodiment, the step of determining the exercise prompt content corresponding to the object to be analyzed according to the muscle group strength includes:

[0016] Determine the preset exercise time corresponding to the muscle group strength, obtain the exercise time and compare it with the preset exercise time;

[0017] When the exercise time is greater than or equal to the preset exercise time, a prompt message is outputted indicating that continuing the exercise may cause muscle strain.

[0018] In one embodiment, after the steps of determining the preset exercise time corresponding to the muscle group strength and obtaining the exercise time for comparison with the preset exercise time, the method further comprises:

[0019] When the exercise time is less than the preset exercise time, according to the difference between the preset exercise time and the exercise time;

[0020] Determining whether the difference is greater than a preset value;

[0021] When the difference is less than the preset value, outputting a prompt message indicating that the exercise intensity is insufficient;

[0022] When the difference is greater than or equal to the preset value, a prompt message indicating that the exercise intensity is too high is output.

[0023] In one embodiment, the step of determining the exercise prompt content corresponding to the object to be analyzed according to the muscle group strength includes:

[0024] Determining whether the strength of the current action is greater than a preset strength according to the muscle group strength;

[0025] When the force of the current action is greater than the preset force, outputting a prompt message that the force may cause muscle damage;

[0026] When the force of the current action is greater than the preset force, a prompt message is outputted indicating that the force cannot reach the exercise intensity.

[0027] In one embodiment, the step of determining the strain of the object to be analyzed within the skin marker point acquisition period according to the skin marker points, and determining the human body three-dimensional structure information corresponding to the object to be analyzed according to the skin marker points includes:

[0028] Determine the image feature values ​​corresponding to the skin marker points at different times;

[0029] The strain condition of the object to be analyzed within a skin marker point acquisition period is determined according to the image feature value, and the three-dimensional structure information of the human body corresponding to the object to be analyzed is acquired according to the image feature value.

[0030] In one embodiment, the steps of determining the strain condition of the object to be analyzed during the skin marker point acquisition period according to the image feature value, and acquiring the human body three-dimensional structure information corresponding to the object to be analyzed according to the image feature value include:

[0031] Determining a change trend of the image feature value and identifying a three-dimensional structural feature of a human body in the image feature value;

[0032] The strain condition of the object to be analyzed during the skin marker point acquisition period is obtained according to the change trend, and the three-dimensional structure information of the human body corresponding to the object to be analyzed is obtained according to the three-dimensional structure features of the human body in the image feature values.

[0033] An embodiment of the present invention also provides a device for determining motion prompts, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, each step of the method for determining motion prompts as described above is implemented.

[0034] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, each step of the method for determining a motion prompt as described above is implemented.

[0035] In the technical solution of the present embodiment, the device for determining the motion prompt obtains skin marker points corresponding to the object to be analyzed collected at different times, and the skin marker points include color marks and / or light spot marks; determines the strain condition of the object to be analyzed during the skin marker point collection period according to the skin marker points, and determines the three-dimensional structure information of the human body corresponding to the object to be analyzed according to the skin marker points, and the three-dimensional structure information of the human body includes geometric information of the skeleton and muscles; determines the muscle group strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body; and determines the motion prompt content corresponding to the object to be analyzed according to the muscle group strength.

[0036] Since people with different physiques have different muscle strengths, if the same exercise prompt content is directly pushed to the pushed group without considering the personal physical characteristics of the pushed group, the pushed exercise prompt content will not be suitable for the pushed group. Taking the above problems into consideration, the exercise prompt determination device of the present invention can determine the muscle group strength information based on the skin marker points of the object to be analyzed. Therefore, corresponding exercise prompt information can be output based on the muscle group strength information. Compared with the existing exercise prompt methods, different exercise prompts can be output for different analysis objects, and customized push can be realized. Without considering the group attributes, pushing according to personal attributes can reduce the limitations of the exercise prompts. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 A schematic diagram of the hardware architecture of a device for determining a motion prompt according to an embodiment of the present invention;

[0039] Figure 2 It is a flowchart of a first embodiment of a method for determining a motion prompt of the present invention;

[0040] Figure 3 It is a flow chart of a second embodiment of a method for determining a motion prompt of the present invention;

[0041] Figure 4 This is a detailed flowchart of step S40 of the third embodiment of the method for determining a motion prompt of the present invention;

[0042] Figure 5 This is a detailed flowchart of step S20 of the fourth embodiment of the method for determining a motion prompt of the present invention. DETAILED DESCRIPTION

[0043] In order to better understand the above technical solution, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0044] The main solution of the present invention is: the motion prompt determination device obtains skin marker points corresponding to the object to be analyzed collected at different times, and the skin marker points include color marks and / or light spot marks; determines the strain condition of the object to be analyzed during the skin marker point collection period according to the skin marker points, and determines the three-dimensional human body structure information corresponding to the object to be analyzed according to the skin marker points, and the three-dimensional human body structure information includes geometric information of the skeleton and muscles; determines the muscle group strength of the object to be analyzed according to the strain condition and the three-dimensional human body structure information; determines the motion prompt content corresponding to the object to be analyzed according to the muscle group strength.

[0045] Since people with different physiques have different muscle strengths, if the same exercise prompt content is directly pushed to the pushed group without considering the personal physical characteristics of the pushed group, the pushed exercise prompt content will not be suitable for the pushed group. Taking the above problems into consideration, the exercise prompt determination device of the present invention can determine the muscle group strength information based on the skin marker points of the object to be analyzed. Therefore, corresponding exercise prompt information can be output based on the muscle group strength information. Compared with the existing exercise prompt methods, different exercise prompts can be output for different analysis objects, and customized push can be realized. Without considering the group attributes, pushing according to personal attributes can reduce the limitations of the exercise prompts.

[0046] As an implementation method, the motion prompt determination device can be as follows: Figure 1 .

[0047] The embodiment of the present invention relates to a device for determining a motion prompt, which includes: a processor 101, such as a CPU, a memory 102, and a communication bus 103. The communication bus 103 is used to realize connection and communication between these components.

[0048] The memory 102 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. Figure 1 , the memory 103 as a computer-readable storage medium may include a detection program; and the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0049] Acquire skin marking points corresponding to the object to be analyzed collected at different times, wherein the skin marking points include color markings and / or light spot markings;

[0050] Determine the strain of the object to be analyzed within the skin marker point acquisition period according to the skin marker points, and determine the three-dimensional human body structure information corresponding to the object to be analyzed according to the skin marker points, wherein the three-dimensional human body structure information includes geometric information of the skeleton and muscles;

[0051] Determine the muscle strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body;

[0052] The exercise prompt content corresponding to the object to be analyzed is determined according to the muscle group strength.

[0053] In one embodiment, the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0054] Inputting the skin marker points into a muscle group strength determination model, wherein the muscle group strength determination model determines the corresponding strain conditions according to the skin marker points, and obtains the three-dimensional structure information of the human body corresponding to the skin marker points;

[0055] The step of determining the muscle strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body comprises:

[0056] The muscle group strength output by the muscle group strength determination model is obtained, wherein the muscle group strength determination model obtains and outputs the corresponding muscle group strength according to the strain condition and the three-dimensional structure information of the human body.

[0057] In one embodiment, the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0058] Acquire a training set, wherein the training set includes skin marker point samples and muscle group strength samples;

[0059] Model training is performed on the model to be trained according to the training set to obtain the muscle group strength determination model.

[0060] In one embodiment, the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0061] Determine the preset exercise time corresponding to the muscle group strength, obtain the exercise time and compare it with the preset exercise time;

[0062] When the exercise time is greater than or equal to the preset exercise time, a prompt message is outputted indicating that continuing the exercise may cause muscle strain.

[0063] In one embodiment, the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0064] When the exercise time is less than the preset exercise time, according to the difference between the preset exercise time and the exercise time;

[0065] Determining whether the difference is greater than a preset value;

[0066] When the difference is less than the preset value, outputting a prompt message indicating that the exercise intensity is insufficient;

[0067] When the difference is greater than or equal to the preset value, a prompt message indicating that the exercise intensity is too high is output.

[0068] In one embodiment, the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0069] Determining whether the strength of the current action is greater than a preset strength according to the muscle group strength;

[0070] When the force of the current action is greater than the preset force, outputting a prompt message that the force may cause muscle damage;

[0071] When the force of the current action is greater than the preset force, a prompt message is outputted indicating that the force cannot reach the exercise intensity.

[0072] In one embodiment, the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0073] Determine the image feature values ​​corresponding to the skin marker points at different times;

[0074] The strain condition of the object to be analyzed within a skin marker point acquisition period is determined according to the image feature value, and the three-dimensional structure information of the human body corresponding to the object to be analyzed is acquired according to the image feature value.

[0075] In one embodiment, the processor 101 may be used to call the detection program stored in the memory 102 and perform the following operations:

[0076] Determining a change trend of the image feature value and identifying a three-dimensional structural feature of a human body in the image feature value;

[0077] The strain condition of the object to be analyzed during the skin marker point acquisition period is obtained according to the change trend, and the three-dimensional structure information of the human body corresponding to the object to be analyzed is obtained according to the three-dimensional structure features of the human body in the image feature values.

[0078] In the technical solution of the present embodiment, the device for determining the motion prompt obtains skin marker points corresponding to the object to be analyzed collected at different times, and the skin marker points include color marks and / or light spot marks; determines the strain condition of the object to be analyzed during the skin marker point collection period according to the skin marker points, and determines the three-dimensional structure information of the human body corresponding to the object to be analyzed according to the skin marker points, and the three-dimensional structure information of the human body includes geometric information of the skeleton and muscles; determines the muscle group strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body; and determines the motion prompt content corresponding to the object to be analyzed according to the muscle group strength. Since people with different physiques have different muscle strengths, if the same exercise prompt content is directly pushed to the pushed group without considering the personal physical characteristics of the pushed group, the pushed exercise prompt content will not be suitable for the pushed group. Taking the above problems into consideration, the exercise prompt determination device of the present invention can determine the muscle group strength information based on the skin marker points of the object to be analyzed. Therefore, corresponding exercise prompt information can be output based on the muscle group strength information. Compared with the existing exercise prompt methods, different exercise prompts can be output for different analysis objects, and customized push can be realized. Without considering the group attributes, pushing according to personal attributes can reduce the limitations of the exercise prompts.

[0079] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0080] Reference Figure 2 , Figure 2 The first embodiment of the method for determining a motion prompt of the present invention comprises the following steps:

[0081] Step S10, obtaining skin marker points corresponding to the object to be analyzed collected at different times, wherein the skin marker points include color markers and / or light spot markers.

[0082] In this embodiment, skin marker points are acquired by identifying images corresponding to the object to be analyzed collected at different times. The images corresponding to the object to be analyzed collected at different times may be video images, wherein the object to be analyzed may be part of the user's limbs, such as arms, abdomen, or legs and other objects carrying muscle groups. Furthermore, the above-mentioned images may be speckle images or high-definition images, and the high-definition images may be taken by a high-definition camera.

[0083] Optionally, the motion prompt determination device actively acquires images corresponding to the object to be analyzed collected at different times;

[0084] Optionally, upon receiving an instruction input by a user, the motion prompt determination device passively acquires images corresponding to the object to be analyzed collected at different times.

[0085] In this embodiment, the object to be analyzed may be a part of the user's limbs, such as an arm, abdomen, or leg, etc., which carries muscle groups, and the skin markers are image information corresponding to the object to be analyzed.

[0086] Step S20, determining the strain of the object to be analyzed during the skin marker point acquisition period according to the skin marker points, and determining the human body three-dimensional structure information corresponding to the object to be analyzed according to the skin marker points, wherein the human body three-dimensional structure information includes geometric information of the skeleton and muscles.

[0087] In this embodiment, the digital image correlation analysis technology (Digital Image Correlation) is used to analyze the changes in the imaging feature points adjacent to the skin marker points, obtain the deformation (strain) of the object to be analyzed, and further combine the three-dimensional structure information of the human body to determine the muscle group where the analysis area is located, so as to obtain accurate and quantitative muscle application conditions and provide targeted guidance for muscle training. Digital image correlation technology is a measurement method for optically measuring the mechanical strain of materials, also known as DIC image processing technology. This method tracks the deformation process of the speckle pattern on the surface of the object, calculates the change in the gray value of the speckle domain, and thus obtains the deformation and strain data of the surface of the object being measured. According to the different ways of obtaining the skin marker points and the calculation results, the digital image correlation method is also divided into two-dimensional DIC and three-dimensional DIC.

[0088] Step S30, determining the muscle strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body.

[0089] In this embodiment, the muscle group strength is the strength of the muscle group of the object to be analyzed determined based on the above-mentioned skin marker points. The muscle group refers to a group of muscles of the same or adjacent parts with unified functions. The purpose of understanding the muscle groups of various parts of the human body is to understand the differences in the types, functions and functions of each muscle, so as to correctly complete various bodybuilding movements, promote the development of muscles in various parts, increase the volume of muscle blocks, make muscles bulge, and make the lines clear. Muscles are widely distributed in the human body. There are about 639 muscles in the whole body, which account for almost 40-50% of the body weight. It can be seen that human muscles are the main body of the body. Their names are generally classified according to the type, shape, position, function, etc. of the muscles.

[0090] Step S40: determining the exercise prompt content corresponding to the object to be analyzed according to the muscle group strength.

[0091] In this embodiment, the muscle strength of different users is often different. Therefore, this embodiment pushes exercise prompt content based on the obtained muscle strength corresponding to the object to be analyzed.

[0092] In the technical solution of this embodiment, since people of different physiques have different muscle strengths, if the personal physical characteristics of the pushed people are not considered and the same exercise prompt content is directly pushed to the pushed people, the pushed exercise prompt content will not be suitable for the pushed people. Taking the above problems into consideration, the exercise prompt determination device of the present invention can determine the muscle strength information based on the skin markers of the object to be analyzed. Therefore, the corresponding exercise prompt information can be output based on the muscle strength information. Compared with the existing exercise prompt methods, different exercise prompts can be output for different analysis objects, and customized push can be realized. Without considering the group attributes, pushing according to personal attributes can reduce the limitations of the exercise prompts.

[0093] Reference Figure 3 , Figure 3 This is a second embodiment of the method for determining a motion prompt of the present invention, based on the first embodiment, step S20 includes:

[0094] Step S21, inputting the skin marker points into a muscle group strength determination model, wherein the muscle group strength determination model determines the corresponding strain conditions according to the skin marker points, and obtains the three-dimensional structure information of the human body corresponding to the skin marker points.

[0095] Step S30 includes:

[0096] Step S31, obtaining the muscle group strength output by the muscle group strength determination model, wherein the muscle group strength determination model obtains and outputs the corresponding muscle group strength according to the strain condition and the three-dimensional structure information of the human body.

[0097] In this embodiment, the muscle group strength determination model is a pre-set mathematical model, which is a scientific or engineering model constructed using mathematical logic methods and mathematical language. Among them, the muscle group strength determination model in this embodiment is preferably a deep learning model.

[0098] Optionally, the muscle group strength determination model is a pre-trained neural network model, and the skin marker points can be input into the pre-trained neural network model to obtain the muscle group strength output by the neural network model. Neural Networks (NN) is a complex network system formed by a large number of simple processing units (called neurons) that are widely interconnected. It reflects many basic characteristics of human brain functions and is a highly complex nonlinear dynamic learning system.

[0099] In this embodiment, the skin marker points are input into a preset muscle group strength determination model, and the muscle group strength output by the muscle group strength determination model can be directly obtained, thereby improving data acquisition efficiency.

[0100] Optionally, for the training method of the neural network model, a training set can be first obtained, the training set including skin marker point samples and muscle group strength samples, and then the model to be trained is trained according to the training set; when the loss function corresponding to the model to be trained converges, the model to be trained is used as the neural network model.

[0101] In the technical solution of this embodiment, by constructing a neural network model, the efficiency and prediction accuracy can be improved when determining the motion prompt content.

[0102] Reference Figure 4 , Figure 4 The third embodiment of the method for determining a motion prompt of the present invention is based on any one of the first to second embodiments, and step S40 includes:

[0103] Step S41, determining the preset exercise time corresponding to the muscle group strength, obtaining the exercise time and comparing it with the preset exercise time.

[0104] In this embodiment, the associated training time is determined according to the above-mentioned muscle group strength, wherein the above-mentioned association relationship can be determined based on the user's physical fitness and muscle group strength collected in advance. For example: when the muscle group strength is A, and the physical fitness corresponding to A is weak, the preset training time is determined based on the above-mentioned corresponding situation.

[0105] Step S42, when the exercise time is greater than or equal to the preset exercise time, output a prompt message that continuing the exercise may cause muscle strain.

[0106] Optionally, when the exercise time is less than the preset exercise time, determine whether the difference is greater than a preset value based on the difference between the preset exercise time and the exercise time; and when the difference is greater than or equal to the preset value, output a prompt message that the exercise intensity is too high.

[0107] Optionally, determine whether the force of the current action is greater than a preset force based on the muscle group strength; if the force of the current action is greater than the preset force, output a prompt message that the force may cause muscle damage; if the force of the current action is greater than the preset force, output a prompt message that the force cannot reach the exercise intensity.

[0108] In the technical solution of this embodiment, the muscle strength of different users may be different, and this situation indirectly highlights the different physiques of different users. This embodiment takes into account that users with different physiques should have different amounts of exercise when performing reasonable exercises. Therefore, this embodiment monitors the exercise time based on the muscle strength corresponding to the object to be analyzed. When it is determined that the time length corresponding to the muscle strength is low and close to the time the user has exercised, exercise prompts about the exercise time can be given, which effectively controls the user's excessive training or poor training results, improves the user's ability to control reasonable exercise time, and also improves the user's safety during exercise.

[0109] Reference Figure 5 , Figure 5 This is a fourth embodiment of the method for determining a motion prompt of the present invention, based on any one of the first to third embodiments, step S20 includes:

[0110] Step S22, determining the image feature values ​​corresponding to the skin marker points at different times.

[0111] Step S23, determining the strain condition of the object to be analyzed during the skin marker point acquisition period according to the image feature value, and acquiring the human body three-dimensional structure information corresponding to the object to be analyzed according to the image feature value.

[0112] In this embodiment, the image feature value is the binary data corresponding to the image feature. The image feature value is used to record the image feature of the image, which can reduce the storage space occupied. Furthermore, the strain condition of the object to be analyzed during the skin marker point acquisition period can be determined based on the comparison of the image feature values, and the target image feature value having a similarity with the three-dimensional structure feature of the human body higher than a preset similarity can be determined based on the comparison of the pre-stored three-dimensional structure feature of the human body with the obtained image feature value, and the image area corresponding to the target image feature value is determined as the area where the skeleton is located. The motion prompt can be determined based on the obtained strain condition and the three-dimensional structure information of the human body.

[0113] Optionally, determine the change trend of the image feature value and identify the human body three-dimensional structure features in the image feature value; obtain the strain of the object to be analyzed during the skin marker point acquisition period according to the change trend, and obtain the human body three-dimensional structure information corresponding to the object to be analyzed according to the human body three-dimensional structure features in the image feature value. The human body three-dimensional structure features are obtained by comparing with preset human body three-dimensional structure feature values.

[0114] In the technical solution of this embodiment, the strain condition corresponding to the object to be analyzed and the three-dimensional structure information of the human body corresponding to the object to be analyzed can be quickly determined through feature comparison, thereby improving the efficiency of determining motion prompts.

[0115] To achieve the above-mentioned purpose, an embodiment of the present invention also provides a device for determining motion prompts, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, it implements the various steps of the method for determining motion prompts as described above.

[0116] To achieve the above objectives, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various steps of the method for determining a motion prompt as described above are implemented.

[0117] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0118] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0119] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0121] It should be noted that in the claims, any reference signs placed between brackets shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claim. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0122] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0123] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for determining a motion prompt, characterized in that: The method for determining the motion prompt comprises the following steps: Acquire skin markers corresponding to the object to be analyzed collected at different times, wherein the skin markers include color markers and / or light spot markers, and the skin markers are acquired by identifying images corresponding to the object to be analyzed collected at different times, wherein the images corresponding to the object to be analyzed collected at different times are video images, speckle images, and high-definition images, and the object to be analyzed is a part of a user's limbs; Determine the strain of the object to be analyzed within the skin marker point acquisition period according to the skin marker points, and determine the three-dimensional human body structure information corresponding to the object to be analyzed according to the skin marker points, wherein the three-dimensional human body structure information includes geometric information of the skeleton and muscles; Determine the muscle strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body; Determining the exercise prompt content corresponding to the object to be analyzed according to the muscle group strength; The steps of determining the strain of the object to be analyzed within the skin marker point acquisition period according to the skin marker points, and determining the human body three-dimensional structure information corresponding to the object to be analyzed according to the skin marker points include: Inputting the skin marker points into a muscle group strength determination model, wherein the muscle group strength determination model determines the corresponding strain conditions according to the skin marker points, and obtains the three-dimensional structure information of the human body corresponding to the skin marker points; The step of determining the muscle strength of the object to be analyzed according to the strain condition and the three-dimensional structure information of the human body comprises: The muscle group strength output by the muscle group strength determination model is obtained, wherein the muscle group strength determination model obtains and outputs the corresponding muscle group strength according to the strain condition and the three-dimensional structure information of the human body.

2. The method for determining a motion prompt according to claim 1, characterized in that: Before the step of acquiring skin marker points corresponding to the object to be analyzed collected at different times, the method further includes: Acquire a training set, wherein the training set includes skin marker point samples and muscle group strength samples; Model training is performed on the model to be trained according to the training set to obtain the muscle group strength determination model.

3. The method for determining a motion prompt according to claim 1, wherein: The step of determining the exercise prompt content corresponding to the object to be analyzed according to the muscle group strength comprises: Determine the preset exercise time corresponding to the muscle group strength, obtain the exercise time and compare it with the preset exercise time; When the exercise time is greater than or equal to the preset exercise time, a prompt message is outputted indicating that continuing the exercise may cause muscle strain.

4. The method for determining a motion prompt according to claim 3, characterized in that: After the steps of determining the preset exercise time corresponding to the muscle group strength and obtaining the exercise time for comparison with the preset exercise time, the method further comprises: When the exercise time is less than the preset exercise time, according to the difference between the preset exercise time and the exercise time; Determining whether the difference is greater than a preset value; When the difference is less than the preset value, outputting a prompt message indicating that the exercise intensity is insufficient; When the difference is greater than or equal to the preset value, a prompt message indicating that the exercise intensity is too high is output.

5. The method for determining a motion prompt according to claim 1, wherein: The step of determining the exercise prompt content corresponding to the object to be analyzed according to the muscle group strength comprises: Determining whether the strength of the current action is greater than a preset strength according to the muscle group strength; When the force of the current action is greater than the preset force, outputting a prompt message that the force may cause muscle damage; When the force of the current action is greater than the preset force, a prompt message is outputted indicating that the force cannot reach the exercise intensity.

6. The method for determining a motion prompt according to claim 1, wherein: The steps of determining the strain of the object to be analyzed within the skin marker point acquisition period according to the skin marker points, and determining the human body three-dimensional structure information corresponding to the object to be analyzed according to the skin marker points include: Determine the image feature values ​​corresponding to the skin marker points at different times; The strain condition of the object to be analyzed within a skin marker point acquisition period is determined according to the image feature value, and the three-dimensional structure information of the human body corresponding to the object to be analyzed is acquired according to the image feature value.

7. The method for determining a motion prompt according to claim 6, wherein: The steps of determining the strain condition of the object to be analyzed within the skin marker point acquisition period according to the image feature value, and acquiring the human body three-dimensional structure information corresponding to the object to be analyzed according to the image feature value include: Determining a change trend of the image feature value and identifying a three-dimensional structural feature of a human body in the image feature value; The strain condition of the object to be analyzed during the skin marker point acquisition period is obtained according to the change trend, and the three-dimensional structure information of the human body corresponding to the object to be analyzed is obtained according to the three-dimensional structure features of the human body in the image feature values.

8. A device for determining a motion prompt, characterized in that: The apparatus for determining motion prompts comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for determining motion prompts as described in any one of claims 1 to 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for determining a motion prompt according to any one of claims 1 to 7 are implemented.

Images