Rope skipping exercise safety early warning method based on image recognition

Abstract

The invention relates to a rope skipping exercise safety early warning method based on image recognition, and relates to the field of rope skipping exercise monitoring, and the method comprises the steps: obtaining image information when a user skips a rope, generating a panoramic image, obtaining a grip strength value of a handle, judging whether an obstacle exists in a preset range of the user or not based on the panoramic image, and if not, judging whether the obstacle exists or not; if yes, the posture of the user and the state of the rope body are determined based on the panoramic image, the risk coefficient that the user is tripped during rope skipping is determined based on the grip value, the posture and the state, and if the risk coefficient reaches a preset coefficient threshold value, the handle is controlled to send out first alarm information. The rope skipping method has the effect of reducing the risk that the user is stumbled during rope skipping.

Description

Technical Field

[0001] The present application relates to the field of rope skipping exercise monitoring, and in particular to a rope skipping exercise safety warning method based on image recognition. Background Art

[0002] Rope skipping is an excellent fitness exercise that can effectively train the coordination of the limbs and the cardiopulmonary function, helping to maintain a healthy body and thus achieve the purpose of strengthening the body. Rope skipping can train people's mathematical concepts, improve memory, cultivate a sense of rhythm and balance, and cultivate direction perception.

[0003] The structure and function of the skipping rope in the prior art are relatively simple, and the risk of the user being tripped while skipping cannot be monitored in time. Summary of the invention

[0004] In order to reduce the risk of users tripping while skipping rope, the present application provides a rope skipping exercise safety warning method based on image recognition.

[0005] In the first aspect, the present application provides a rope skipping sports safety warning method based on image recognition, which adopts the following technical solution: A rope skipping sports safety warning method based on image recognition, comprising: Obtain image information of the user while skipping rope and generate a panoramic image, and obtain the grip strength value of the handle; Determining whether there is an obstacle within the user preset range based on the panoramic image; If not, determining the user's posture and the state of the rope body based on the panoramic image; Determining a risk factor of the user tripping while skipping based on the grip strength value, posture and state; If the risk coefficient reaches a preset coefficient threshold, the handle is controlled to issue a first alarm message.

[0006] By adopting the above technical solution, image information of the user when skipping rope is obtained and a panoramic image is generated, and the grip value of the handle is obtained. The panoramic image reflects the user's movement state when the user is skipping rope. The grip value represents the strength of the user's grip on the handle when skipping rope. Based on the panoramic image, it is judged whether there are obstacles within the preset range of the user. If there are obstacles around the user, it may cause the user to be unable to complete the skipping rope exercise normally. When the user can skip rope normally, different postures will be shown from person to person, and the rope body may also show different states due to the influence of the user's strength or external factors. Therefore, if there are no obstacles, the user's posture and the state of the rope body are determined based on the panoramic image. The posture reflects whether the user's movements when skipping rope are standard, and the state represents the standardization of the user's shaking of the rope when skipping rope. The risk coefficient of the user being tripped when skipping rope is determined based on the grip value, posture and state. The risk coefficient represents the possibility of the user being tripped when skipping rope. If the risk coefficient reaches the preset coefficient threshold, the control handle sends a first alarm message, which can timely remind the user that he may be tripped, thereby reducing the risk of the user being tripped.

[0007] In another possible implementation, the determining the risk factor of the user tripping while skipping rope based on the grip strength value, posture, and state includes: Determining, based on the posture, a bending angle of the user's knees and a height of the user's toes from the ground when the user jumps; Determining a rope swing score of the rope body based on the state; determining a minimum value of the grip strength value; The risk factor of the user tripping while rope skipping is determined based on the minimum value, the bending angle, the height from the ground, the rope swing score and the respective first coefficients.

[0008] In another possible implementation, determining the rope swing score of the rope body based on the state includes: determining a similarity between the state and a predetermined state; Determine the rope length when the rope body is in contact with the ground based on the state; Determine the distance between the midpoint of the rope length and the toe; The rope swing score of the rope body is determined based on the similarity, rope length, distance and respective second coefficients.

[0009] In another possible implementation, the method further includes: Get the highest rope skipping count in history of the user; Determine the current rope skipping count of the user based on the panoramic image; When the current rope skipping count exceeds the historical highest rope skipping count, determining the user's facial state; Whether the user needs a rest is determined based on the facial state.

[0010] In another possible implementation, judging whether the user needs a rest based on the facial state includes: Determining a skin color value of the user's face based on the facial state; It is determined whether the skin color value is within a preset skin color range, and then it is determined whether the user needs a rest.

[0011] In another possible implementation, the method further includes: If a rest is needed, a second alarm message is output.

[0012] In another possible implementation, the method further includes: Determine the movement trajectory of the user based on the panoramic image; Determine the moving step length of each jump of the user based on the moving trajectory; When there is a moving step length exceeding a preset step length threshold, determining a difference between the moving step length and the preset step length threshold; The risk factor is adjusted based on the difference.

[0013] In a second aspect, the present application provides a skipping rope, which adopts the following technical solution: A skipping rope, comprising: Two handles; A rope body connecting the two handles; The pressure sensors installed on the two handles are used to collect the grip strength of the handles when the user is skipping rope; A processor, wherein the two pressure sensors are both communicatively connected to the processor; At least one camera, used to collect image information of the user when skipping rope, the camera is communicatively connected with the processor; Memory; At least one application, wherein the at least one application is stored in the memory and is configured to be executed by the at least one processor, and the at least one application is used to execute a rope skipping sports safety warning method based on image recognition according to any one of claims 1 to 7.

[0014] In a third aspect, the present application provides a rope skipping sports safety warning device based on image recognition, which adopts the following technical solution: A rope skipping sports safety warning device based on image recognition, comprising: The first acquisition module is used to acquire image information of the user when skipping rope and generate a panoramic image, and acquire the grip strength value of the handle; A first judgment module, used to judge whether there is an obstacle within the user preset range based on the panoramic image; A first determination module, configured to determine the user's posture and the state of the rope body based on the panoramic image if the state does not exist; A second determination module is used to determine the risk factor of the user tripping while skipping based on the grip strength value, posture and state; The control module is used to control the handle to issue a first alarm message if the risk coefficient reaches a preset coefficient threshold.

[0015] By adopting the above technical solution, the first acquisition module obtains image information when the user is skipping rope and generates a panoramic image, and obtains the grip value of the handle. The panoramic image reflects the user's movement state when the user is skipping rope, and the grip value represents the grip strength of the user on the handle when the user is skipping rope. The first judgment module determines whether there are obstacles within the preset range of the user based on the panoramic image. If there are obstacles around the user, the user may not be able to complete the skipping rope exercise normally. When the user can skip rope normally, different postures will be shown depending on the user, and the rope body may also show different states due to the influence of the user's strength or external factors. Therefore, if there are no obstacles, the first determination module determines the user's posture and the state of the rope body based on the panoramic image. The posture reflects whether the user's movements when skipping rope are standard, and the state represents the standardization of the user's shaking of the rope when skipping rope. The second determination module determines the risk factor of the user being tripped when skipping rope based on the grip value, posture and state. The risk factor represents the possibility of the user being tripped when skipping rope. If the risk factor reaches the preset coefficient threshold, the control module controls the handle to send a first alarm message, which can timely remind the user that he may be tripped, thereby reducing the risk of the user being tripped.

[0016] In another possible implementation, when the second determination module determines the risk factor of the user tripping while skipping rope based on the grip strength value, posture and state, it is specifically configured to: Determining, based on the posture, a bending angle of the user's knees and a height of the user's toes from the ground when the user jumps; Determining a rope swing score of the rope body based on the state; determining a minimum value of the grip strength value; The risk factor of the user tripping while rope skipping is determined based on the minimum value, the bending angle, the height from the ground, the rope swing score and the respective first coefficients.

[0017] In another possible implementation, when determining the rope swing score of the rope body based on the state, the second determination module is specifically configured to: determining a similarity between the state and a predetermined state; Determine the rope length when the rope body is in contact with the ground based on the state; Determine the distance between the midpoint of the rope length and the toe; The rope swing score of the rope body is determined based on the similarity, rope length, distance and respective second coefficients.

[0018] In another possible implementation, the device further includes: A second acquisition module is used to acquire the highest rope skipping count in history of the user; A third determination module, configured to determine a current rope skipping count of the user based on the panoramic image; a fourth determination module, configured to determine the facial state of the user when the current rope skipping count exceeds the historical highest rope skipping count; The second judgment module is used to judge whether the user needs a rest based on the facial state.

[0019] In another possible implementation, when the second determination module determines whether the user needs a rest based on the facial state, it is specifically configured to: Determining a skin color value of the user's face based on the facial state; It is determined whether the skin color value is within a preset skin color range, and then it is determined whether the user needs a rest.

[0020] In another possible implementation, the device further includes: The output module is used to output a second alarm message if a rest is needed.

[0021] In another possible implementation, the device further includes: A movement trajectory determination module, used to determine the movement trajectory of the user based on the panoramic image; A moving step length determination module, used to determine the moving step length of each jump of the user based on the moving trajectory; A difference determination module, used for determining the difference between the moving step length and the preset step length threshold when there is a moving step length exceeding the preset step length threshold; An adjustment module is used to adjust the risk factor based on the difference.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium, when the computer program is executed in a computer, enables the computer to execute the rope skipping sports safety warning method based on image recognition as described in any one of the first aspects.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: The image information of the user when jumping rope is obtained and a panoramic image is generated, and the grip value of the handle is obtained. The panoramic image reflects the user's movement state when the user is jumping rope. The grip value represents the strength of the user's grip on the handle when jumping rope. Based on the panoramic image, it is judged whether there are obstacles within the user's preset range. If there are obstacles around the user, the user may not be able to complete the skipping exercise normally. When the user can jump rope normally, different postures will be shown from person to person, and the rope body may also show different states due to the influence of the user's strength or external factors. Therefore, if there are no obstacles, the user's posture and the state of the rope body are determined based on the panoramic image. The posture reflects whether the user's movements when jumping rope are standard, and the state represents the standardization of the user's shaking of the rope when jumping rope. The risk coefficient of the user being tripped when jumping rope is determined based on the grip value, posture and state. The risk coefficient represents the possibility of the user being tripped when jumping rope. If the risk coefficient reaches the preset coefficient threshold, the control handle sends a first alarm message, which can timely remind the user that he may be tripped, thereby reducing the risk of the user being tripped. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flow chart of a rope skipping sports safety warning method based on image recognition in an embodiment of the present application.

[0025] Figure 2 It is a structural schematic diagram of a skipping rope in an embodiment of the present application.

[0026] Figure 3 This is another structural schematic diagram of a skipping rope in an embodiment of the present application.

[0027] Figure 4 It is a structural schematic diagram of a rope skipping sports safety warning device based on image recognition in an embodiment of the present application.

[0028] Figure numerals: 2, skipping rope; 21, handle; 211, pressure sensor; 212, camera; 22, rope body; 23, processor; 24, bus; 25, memory; 26, transceiver. DETAILED DESCRIPTION

[0029] The present application is further described in detail below in conjunction with the accompanying drawings.

[0030] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0031] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0032] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0033] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0034] The embodiment of the present application provides a rope skipping sports safety warning method based on image recognition, which is executed by the rope skipping system, such as Figure 1 As shown, the method includes step S101, step S102, step S103, step S104 and step S105, wherein: S101, obtaining image information of a user skipping rope and generating a panoramic image, and obtaining a grip strength value of a handle.

[0035] For the embodiment of the present application, the cameras installed on the skipping rope are connected to the processor for communication, and each of them collects image information of the corresponding range. The processor inside the skipping rope obtains the image information and merges it to generate a panoramic image of the user when skipping rope.

[0036] Among them, Figure 2 As shown, a pressure sensor 211 is arranged on the annular surface of the handle 21. The pressure sensors 211 arranged on the two handles 21 are at the same position and are used to collect the grip strength value of the handle 21. The processor inside the skipping rope 2 obtains the grip strength value of the handle 21 when the user skips rope.

[0037] The skipping rope 2 includes cameras 212 arranged on the skipping rope 2, which can be 10 cameras 212, with 5 cameras 212 arranged on each handle 21. For one handle 21, one camera is arranged on the upper side of the annular surface of the end of the handle 21 close to the rope body 22, for collecting the facial state of the user when skipping rope, one camera is arranged on the lower side of the annular surface of the end of the handle 21 close to the rope body 22, for collecting the user's posture when skipping rope, two cameras are arranged on the annular surface of the end of the handle 21 away from the rope body 22 and facing the upper side and the lower side respectively, and one camera is arranged on the end face of the end of the handle 21 away from the rope body 22 and facing outward, for collecting the external environment when the user is skipping rope. The cameras 212 arranged on the two handles 21 are in the same position, and the 8 cameras 212 each collect image information of the corresponding range. The processor inside the skipping rope 2 obtains the image information and merges it to generate a panoramic image of the user when skipping rope.

[0038] S102: Determine whether there is an obstacle within a range preset by the user based on the panoramic image.

[0039] In the embodiment of the present application, the processor inside the skipping rope inputs the panoramic image into the trained network model for obstacle recognition, and then determines whether there are obstacles within the user's preset range. Specifically, the network model can be a convolutional neural network model, a recurrent neural network model, or other types of network models, which are not limited here.

[0040] S103: If not, determine the user's posture and the state of the rope based on the panoramic image.

[0041] For the embodiment of the present application, if there are no obstacles, the processor inside the skipping rope will input the panoramic image into the trained network model to perform user posture recognition and rope body recognition, and then determine the user's posture and the state of the rope. The posture reflects whether the user's movements when skipping rope are standard, and the state represents the standardization of the user's rope shaking when skipping rope.

[0042] S104, determining the risk factor of the user tripping while skipping based on the grip strength value, posture and state.

[0043] For the embodiment of the present application, the processor inside the skipping rope determines the risk factor of the user tripping while skipping based on the grip strength value, posture and state. The risk factor represents the possibility of the user tripping while skipping.

[0044] S105: If the risk factor reaches a preset coefficient threshold, the control handle sends a first alarm message.

[0045] In the embodiment of the present application, the processor inside the skipping rope determines the risk factor. If the risk factor reaches a preset coefficient threshold, the control handle sends a first alarm message, which can be a vibration of the handle or a sound prompt of the handle. The risk factor of the user tripping while skipping rope is determined based on the user's posture during skipping rope, the state of the rope body, and the grip value of the handle. If the preset coefficient threshold is reached, the control handle sends a first alarm message, which can promptly remind the user that he may trip, thereby reducing the risk of the user tripping.

[0046] In a possible implementation of the embodiment of the present application, the risk factor of the user tripping while skipping rope is determined based on the grip strength value, posture and state in step S104, which specifically includes steps S1041, S1042, S1043 and S1044, wherein: Step S1041, determining the bending angle of the user's knees and the height of the user's toes from the ground when the user jumps based on the posture.

[0047] For the embodiment of the present application, when the user jumps rope, in order for the rope to pass smoothly under the feet, the user's feet need to leave the ground, and the knees will be bent to a certain extent when jumping. The bending angle of the knees and the height of the toes from the ground are important factors that affect whether the rope can pass smoothly under the feet. Therefore, the processor inside the skipping rope determines the bending angle of the knees and the height of the toes from the ground when the user jumps based on the posture.

[0048] Step S1042, determining the rope swing score based on the state.

[0049] For the embodiment of the present application, when the user is jumping rope, the user's hands may swing up and down or left and right, so the processor inside the skipping rope determines the rope shaking score based on the state.

[0050] Step S1043, determining the minimum value of the grip strength.

[0051] For the embodiment of the present application, when the user is jumping rope, the user's two hands grasp the two handles of the skipping rope. If the strength of the hands grasping the handles is too weak, the handles may fall off, causing the rope to be unable to pass under the feet. Therefore, the processor inside the skipping rope determines the minimum value based on the grip strength values ​​of the two handles. The smaller the grip strength value, the greater the possibility that the user will trip while jumping rope.

[0052] Step S1044, determining the risk factor of the user tripping while skipping rope based on the minimum value, the bending angle, the height from the ground, the rope-swinging score, and the respective first coefficients.

[0053] For the embodiment of the present application, the minimum value reflects the degree of looseness of the user's hands when grasping the handle, the bending angle reflects the degree of bending of the user's knees when jumping, and the height above the ground represents the height of the user from the ground when jumping. The lower the height above the ground, the less likely the body will pass under the feet, making it easier to trip. The rope shaking score represents the standard degree of the user's movements when shaking the rope. Therefore, the processor inside the skipping rope determines the risk coefficient of the user tripping while skipping based on the minimum value, bending angle, height above the ground, rope shaking score and their respective first coefficients. The risk coefficient reflects the possibility of the user tripping while skipping.

[0054] In a possible implementation of the embodiment of the present application, the rope swing score of the rope body is determined based on the state in step S1042, which specifically includes step S1 (not shown in the figure), step S2 (not shown in the figure), step S3 (not shown in the figure) and step S4 (not shown in the figure), wherein: Step S1, determining the similarity between the state and the preset state.

[0055] For the embodiment of the present application, the preset state can be the standard state of the rope body when the user skipped rope in the past. The user can store the preset state in the processor inside the skipping rope in advance. The processor inside the skipping rope determines the similarity between the state and the preset state. The lower the similarity, the less standard the user's rope shaking action is.

[0056] Step S2, determining the rope length when the rope body is in contact with the ground based on the state.

[0057] With respect to the embodiments of the present application, when a user jumps rope, the swung rope will come into contact with the ground. The processor inside the skipping rope determines the length of the rope when the rope is in contact with the ground based on the state. When the user's hand swings greatly, the length of the rope in contact with the ground will be too long. When the hand swings less or the hand is raised too high, the length of the rope in contact with the ground will become shorter. In both cases, the rope may not pass normally under the feet, thereby causing the user to trip.

[0058] Step S3, determining the distance between the midpoint of the rope and the toes.

[0059] For the embodiment of the present application, the processor inside the skipping rope determines the distance between the end point of the rope and the toes. The longer the distance, the greater the risk of tripping because the rope may not reach the feet when the user's feet jump up to the ground.

[0060] Step S4, determining the rope swing score of the rope body based on the similarity, rope length, distance and respective second coefficients.

[0061] For the embodiment of the present application, the similarity represents the standard degree of the rope when the user jumps rope, the rope length represents the length of the rope contact with the ground, and the distance represents the distance between the rope and the toes. All three are important factors affecting the rope shaking score. Therefore, the processor inside the skipping rope calculates the rope shaking score based on the similarity, rope length, distance and their respective second coefficients.

[0062] In a possible implementation manner of the embodiment of the present application, the method further includes step 1, step 2, step 3 and step 4, wherein: Step 1: Get the user's highest rope skipping count in history.

[0063] For the embodiment of the present application, the historical rope skipping counts of the user are stored in the processor inside the rope skipping device, and the processor inside the rope skipping device obtains the highest historical rope skipping count of the user.

[0064] Step 2: Determine the user's current rope skipping count based on the panoramic image.

[0065] For the embodiment of the present application, the processor inside the skipping rope determines the user's current skipping count based on the panoramic image.

[0066] Step three, when the current rope skipping count exceeds the highest rope skipping count in history, determine the user's facial state.

[0067] For the embodiment of the present application, when the current skipping rope count exceeds the highest historical skipping rope count, it means that the user may have reached his or her own exercise limit. Therefore, the processor inside the skipping rope performs facial recognition on the panoramic image to determine the user's facial state, which reflects the user's fatigue level.

[0068] Step 4: Determine whether the user needs a rest based on the facial state.

[0069] For the embodiment of the present application, the processor inside the skipping rope determines whether the user needs a rest based on the facial state.

[0070] In a possible implementation of the embodiment of the present application, in step 4, judging whether the user needs to rest based on the facial state specifically includes step 5 and step 6, wherein: Step 5: Determine the skin color value of the user's face based on the facial state.

[0071] For the embodiment of the present application, when the user jumps rope for too long, the user's face may become pale or red, so the processor inside the skipping rope determines the skin color value of the user's face based on the facial state.

[0072] Step six, determining whether the skin color value is within a preset skin color range, and then determining whether the user needs a rest.

[0073] For the embodiment of the present application, if the user's skin color value is too pale or too reddish, hypoxia or fainting may occur. Therefore, the processor inside the skipping rope judges the user's skin color value to determine whether it is within the preset skin color range. If it exceeds the preset skin color range, it means that the user is too tired and needs to rest immediately.

[0074] In a possible implementation manner of the embodiment of the present application, the method further includes step seven, wherein step seven may be performed after step six, wherein: Step seven: if a rest is needed, output a second alarm message.

[0075] For the embodiment of the present application, if a rest is needed, that is, when the skin color value is not within the preset skin color range, the processor inside the skipping rope outputs a second alarm message. The second alarm message can be a vibration of the handle or a sound of the handle, which is distinguished from the first alarm message.

[0076] In a possible implementation manner of the embodiment of the present application, the method further includes step S5 (not shown in the figure), step S6 (not shown in the figure), step S7 (not shown in the figure) and step S8 (not shown in the figure), wherein step S5 may be performed after step S104, wherein: Step S5: determining the user's movement trajectory based on the panoramic image.

[0077] For the embodiment of the present application, the user will not be completely fixed in the same position when jumping rope, and may move forward and backward or left and right. Therefore, the processor inside the skipping rope determines the user's movement trajectory based on the panoramic image, and the movement trajectory reflects the user's movement.

[0078] Step S6: determining the moving step length of the user each time he jumps based on the moving trajectory.

[0079] For the embodiment of the present application, the processor inside the skipping rope determines the moving step length of the user each jump based on the moving trajectory. The longer the moving step length, the larger the range of movement. If there are obstacles or other people around, the skipping rope may be interrupted, causing the user to trip and may also injure other people.

[0080] Step S7: when there is a movement step length exceeding the preset step length threshold, determine the difference between the movement step length and the preset step length threshold.

[0081] For the embodiment of the present application, the processor inside the skipping rope determines the moving step length. When the moving step length exceeds the preset step length threshold, the difference between the moving step length and the preset step length threshold is determined. The difference reflects the distance exceeding the preset step length threshold.

[0082] Step S8, adjusting the risk factor based on the difference.

[0083] For the embodiment of the present application, the processor inside the skipping rope determines the corresponding adjustment value based on the difference and increases the risk factor by the adjustment value.

[0084] In an embodiment of the present application, a skipping rope is provided, such as Figure 2 and Figure 3 As shown, Figure 2 and Figure 3 The skipping rope 2 shown includes: two handles 21, both of which are cylindrical, a rope body 22 fixedly connected to the two handles 21, a wire is arranged inside the rope body 22, a pressure sensor 211 fixedly connected to the two handles 21, used to collect the grip value of the handles 21 when the user skips rope, a processor 23, a memory 25, the processor 23 and the memory 25 are both arranged inside one of the handles 21, the two pressure sensors 211 are connected to the processor 23 by wires, 10 cameras 212 are used to collect image information when the user skips rope, the camera 212 is connected to the processor 23 by wires, and the pressure sensor 211 and the camera 212 on the other handle 21 are connected to the processor 23 by wires.

[0085] The processor 23 is connected to the memory 25, for example, via a bus 24. Optionally, the skipping rope 2 may further include a transceiver 26. It should be noted that in actual applications, the number of transceivers 26 is not limited to one, and the structure of the skipping rope 2 does not constitute a limitation on the embodiments of the present application.

[0086] The processor 23 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 23 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0087] The bus 24 may include a path for transmitting information between the above components. The bus 24 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 24 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0088] The memory 25 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0089] The memory 25 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 23. The processor 23 is used to execute the application code stored in the memory 25 to implement the contents shown in the above method embodiment.

[0090] in, Figure 2 and Figure 3 The skipping rope shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0091] The following embodiment introduces a rope skipping sports safety warning device based on image recognition from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0092] The present application embodiment provides a rope skipping sports safety warning device 30 based on image recognition, such as Figure 4 As shown, the rope skipping sports safety warning device 30 based on image recognition may specifically include: The first acquisition module 301 is used to acquire image information of the user when skipping rope and generate a panoramic image, and acquire the grip strength value of the handle; The first judging module 302 is used to judge whether there is an obstacle within the range preset by the user based on the panoramic image; A first determination module 303 is used to determine the user's posture and the state of the rope body based on the panoramic image if it does not exist; A second determination module 304 is used to determine the risk factor of the user tripping while skipping based on the grip strength value, posture and state; The control module 305 is used to control the handle to issue a first alarm message if the risk coefficient reaches a preset coefficient threshold.

[0093] The embodiment of the present application discloses a rope skipping sports safety warning device 30 based on image recognition, wherein the first acquisition module 301 acquires image information of a user when skipping rope and generates a panoramic image, and acquires the grip strength value of the handle, the panoramic image reflects the user's motion state when skipping rope, the grip strength value represents the magnitude of the user's grip on the handle when skipping rope, the first judgment module 302 judges whether there are obstacles within the user's preset range based on the panoramic image, if there are obstacles around the user, it may cause the user to be unable to complete the rope skipping exercise normally, and when the user can skip rope normally, different postures may be shown depending on the user, and the rope body may also be affected by the user's strength Or the influence of external factors manifests different states. Therefore, if there is no obstacle, the first determination module 303 determines the user's posture and the state of the rope based on the panoramic image. The posture reflects whether the user's movements when jumping rope are standard, and the state represents the standardization of the user's shaking of the rope when jumping rope. The second determination module 304 determines the risk coefficient of the user tripping when jumping rope based on the grip strength value, posture and state. The risk coefficient represents the possibility of the user tripping when jumping rope. If the risk coefficient reaches the preset coefficient threshold, the control module 305 controls the handle to send a first alarm message, which can promptly remind the user that he may be tripped, thereby reducing the risk of the user tripping.

[0094] In a possible implementation of the embodiment of the present application, when the second determination module 304 determines the risk factor of the user tripping while skipping rope based on the grip strength value, posture and state, it is specifically used to: Determine the bending angle of the user's knees and the height of the toes from the ground when the user jumps based on the posture; Determine the rope swing score of the rope body based on the state; Determine the minimum grip strength value; The risk factor of the user tripping while skipping rope is determined based on the minimum value, the bending angle, the height from the ground, the rope shaking score and the respective first coefficients.

[0095] In a possible implementation of the embodiment of the present application, when the second determination module 304 determines the rope swing score based on the state, it is specifically used to: Determine the similarity between the state and the preset state; Determine the rope length when the rope body is in contact with the ground based on the state; Determine the distance between the midpoint of the rope and the toes; The rope swing score of the rope body is determined based on the similarity, rope length, distance and the respective second coefficients.

[0096] In a possible implementation of the embodiment of the present application, the device 30 further includes: The second acquisition module is used to obtain the user's highest rope skipping count in history; A third determination module, configured to determine a current rope skipping count of the user based on the panoramic image; A fourth determination module, configured to determine the user's facial state when the current rope skipping count exceeds the highest rope skipping count in history; The second judgment module is used to judge whether the user needs a rest based on the facial state.

[0097] In a possible implementation of the embodiment of the present application, when the second judgment module judges whether the user needs to rest based on the facial state, it is specifically used to: Determining a skin color value of the user's face based on the facial state; Determine whether the skin color value is within the preset skin color range, and then determine whether the user needs a rest.

[0098] In a possible implementation of the embodiment of the present application, the device 30 further includes: The output module is used to output a second alarm message if a rest is needed.

[0099] In a possible implementation of the embodiment of the present application, the device 30 further includes: A movement trajectory determination module, used to determine the movement trajectory of the user based on the panoramic image; A moving step length determination module, used to determine the moving step length of the user each time he jumps based on the moving trajectory; A difference determination module, used for determining the difference between the moving step length and the preset step length threshold when there is a moving step length exceeding the preset step length threshold; An adjustment module is used to adjust the risk factor based on the difference.

[0100] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment. Compared with the related art, in the embodiment of the present application, image information of the user when jumping rope is obtained and a panoramic image is generated, and the grip value of the handle is obtained. The panoramic image reflects the user's movement state when the user is jumping rope. The grip value represents the strength of the user's grip on the handle when jumping rope. Based on the panoramic image, it is judged whether there are obstacles within the preset range of the user. If there are obstacles around the user, it may cause the user to be unable to complete the jumping rope exercise normally. When the user can jump rope normally, different postures will be shown depending on the person, and the rope body may also show different states due to the influence of the user's strength or external factors. Therefore, if there are no obstacles, the user's posture and the state of the rope body are determined based on the panoramic image. The posture reflects whether the user's movements when jumping rope are standard, and the state represents the standardization of the user's shaking of the rope when jumping rope. The risk coefficient of the user being tripped when jumping rope is determined based on the grip value, posture and state. The risk coefficient represents the possibility of the user being tripped when jumping rope. If the risk coefficient reaches the preset coefficient threshold, the control handle sends a first alarm message, which can timely remind the user that he may be tripped, thereby reducing the risk of the user being tripped.

[0101] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0102] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A rope skipping sports safety warning method based on image recognition, characterized in that: include: Obtain image information of the user while skipping rope and generate a panoramic image, and obtain the grip strength value of the handle; Determining whether there is an obstacle within the user preset range based on the panoramic image; If not, determining the user's posture and the state of the rope body based on the panoramic image; Determining a risk factor of the user tripping while skipping based on the grip strength value, posture and state; If the risk coefficient reaches a preset coefficient threshold, the handle is controlled to issue a first alarm message.

2. A rope skipping sports safety early warning method based on image recognition according to claim 1, characterized in that: The determining the risk factor of the user tripping while skipping rope based on the grip strength value, posture and state includes: Determining, based on the posture, a bending angle of the user's knees and a height of the user's toes from the ground when the user jumps; Determining a rope swing score of the rope body based on the state; determining a minimum value of the grip strength value; The risk factor of the user tripping while rope skipping is determined based on the minimum value, the bending angle, the height from the ground, the rope swing score and the respective first coefficients.

3. A rope skipping sports safety early warning method based on image recognition according to claim 2, characterized in that: The step of determining the rope swing score of the rope body based on the state comprises: determining a similarity between the state and a predetermined state; Determine the rope length when the rope body is in contact with the ground based on the state; Determine the distance between the midpoint of the rope length and the toe; The rope swing score of the rope body is determined based on the similarity, rope length, distance and respective second coefficients.

4. The rope skipping sports safety early warning method based on image recognition according to claim 1, characterized in that: The method further comprises: Get the highest rope skipping count in history of the user; Determine the current rope skipping count of the user based on the panoramic image; When the current rope skipping count exceeds the historical highest rope skipping count, determining the user's facial state; Whether the user needs a rest is determined based on the facial state.

5. The method for early warning of rope skipping based on image recognition according to claim 4, characterized in that: The determining whether the user needs a rest based on the facial state includes: Determining a skin color value of the user's face based on the facial state; It is determined whether the skin color value is within a preset skin color range, and then it is determined whether the user needs a rest.

6. The rope skipping sports safety early warning method based on image recognition according to claim 5, characterized in that: The method further comprises: If a rest is needed, a second alarm message is output.

7. The method for early warning of rope skipping based on image recognition according to claim 1, characterized in that: The method further comprises: Determine the movement trajectory of the user based on the panoramic image; Determine the moving step length of each jump of the user based on the moving trajectory; When there is a moving step length exceeding a preset step length threshold, determining a difference between the moving step length and the preset step length threshold; The risk factor is adjusted based on the difference.

8. A rope skipping sports safety warning device based on image recognition, characterized in that: include: The first acquisition module is used to acquire the panoramic image and the grip strength value of the handle when the user is skipping rope; A first judgment module, used to judge whether there is an obstacle within the user preset range based on the panoramic image; A first determination module, configured to determine the user's posture and the state of the rope body based on the panoramic image if the state does not exist; A second determination module is used to determine the risk factor of the user tripping while skipping based on the grip strength value, posture and state; The control module is used to control the handle to issue a first alarm message if the risk coefficient reaches a preset coefficient threshold.

9. A skipping rope, characterized in that: It includes: Two handles; A rope body connecting the two handles; The pressure sensors installed on the two handles are used to collect the grip strength of the handles when the user is skipping rope; A processor, wherein the two pressure sensors are both communicatively connected to the processor; At least one camera, used to capture a panoramic image of the user while skipping rope, the camera being communicatively connected to the processor; Memory; At least one application, wherein the at least one application is stored in the memory and is configured to be executed by the at least one processor, and the at least one application is used to execute a rope skipping sports safety warning method based on image recognition according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the rope skipping sports safety warning method based on image recognition as described in any one of claims 1 to 7.

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