Three-dimensional animation human body motion system and control method

Abstract

A three-dimensional animation human body motion system and a control method belong to the technical field of three-dimensional animation human body motion, and are characterized in that steady-state numerical values and corresponding limb motion data of a human body during a human body motion period are collected, and after the collection is finished, cooperative processing is carried out on the steady-state numerical values and the corresponding limb motion data of the human body; the motion condition of the human body is intensively identified according to the steady-state numerical value and the corresponding limb motion data of the human body, the motion condition of the human body is transmitted to the liquid crystal screen connected with the controller to be displayed, and a corresponding reference time point is additionally arranged, so that maintenance after detection is facilitated; whether the measured corresponding limb movement data of the human body accurately reflects the corresponding human body movement condition or not is determined, that is, whether the micro sensor unit fails or not and the measured corresponding limb movement data of the human body cannot accurately reflect the corresponding human body movement condition is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of human body motion of three-dimensional animation, and in particular relates to a human body motion system and a control method of three-dimensional animation. Background Art

[0002] In the human motion system of three-dimensional animation, the existing technical solution such as the patent publication number "CN201431466Y" is often used to display the human motion system of three-dimensional animation. It uses a micro-sensor unit to measure the corresponding limb motion data of the human body, and derives the overall motion parameters of the human body based on this. Finally, the three-dimensional motion image of the human body is driven according to the overall motion parameters of the human body, and the corresponding real-life motion is reproduced in the virtual world in the form of animation. The corresponding limb motion data of the human body includes the three-dimensional curvature, angular velocity, and angular acceleration of the corresponding limbs of the human body.

[0003] Whether the measured corresponding limb movement data of the human body accurately reflects the corresponding human body movement status, that is, whether the micro-sensor unit fails and cannot make the measured corresponding limb movement data of the human body accurately reflect the corresponding human body movement status, there is no relevant technology in the prior art to determine whether the measured corresponding limb movement data of the human body accurately reflects the corresponding human body movement status. Summary of the invention

[0004] In order to solve the defects in the prior art, the present invention proposes a three-dimensional animation human body motion system and method, which collects steady-state values ​​and corresponding limb motion data of the human body during human body motion, and performs coordinated processing on the steady-state values ​​and corresponding limb motion data of the human body after the collection is completed, so as to centrally identify the motion state of the human body based on the steady-state values ​​and the corresponding limb motion data of the human body, and transmit the motion state of the human body to a liquid crystal screen connected to a controller for display, and also provides corresponding reference time points for maintenance after detection; it is achieved to determine whether the measured corresponding limb motion data of the human body accurately reflects the corresponding human body motion state, that is, to determine whether the micro-sensor unit fails and cannot make the measured corresponding limb motion data of the human body accurately reflect the corresponding human body motion state.

[0005] The present invention uses the following technical solutions.

[0006] A control method for a human body motion system of a three-dimensional animation, comprising:

[0007] The controller receives the corresponding limb motion data of the human body measured by the micro sensor unit, and then processes the corresponding limb motion data of the human body, and derives the overall motion parameters of the human body based on the processed corresponding limb motion data of the human body, and finally drives the three-dimensional motion image of the human body based on the overall motion parameters of the human body, and reproduces the corresponding real person motion in the virtual world in the form of animation;

[0008] A method for processing corresponding limb motion data of a human body, comprising:

[0009] Step 1, the controller collects the steady-state values ​​and the corresponding limb movement data of the human body during the human body movement, and performs coordinated processing on the steady-state values ​​and the corresponding limb movement data of the human body after the collection is completed;

[0010] Step 2, after co-processing the steady-state values ​​and the corresponding limb movement data of the human body, the unreasonable data is removed, and the specific movement status of the human body is identified;

[0011] Step 3, transform the conclusion of the human body's movement status and transmit it to the LCD screen connected to the controller for display.

[0012] Furthermore, in Step 1, the corresponding limb motion data of the human body includes the three-dimensional radian, angular velocity, and angular acceleration of the corresponding limb of the human body.

[0013] Furthermore, in Step 1, the steady-state values ​​include the height, weight, and three-dimensional arc of the corresponding limbs of the human body when the human body starts to move.

[0014] Furthermore, in Step 1, the method of co-processing the steady-state value and the corresponding limb movement data of the human body specifically includes:

[0015] Step 1-1, pre-processing the steady-state values ​​and the corresponding limb motion data of the human body to extract the steady-state attribute values ​​and motion attribute values;

[0016] Step 1-2, respectively construct a steady-state model based on the existing parameters and a motion model based on the queue data, and send the extracted steady-state attribute values ​​and motion attribute values ​​into the corresponding models;

[0017] Step 1-3, collecting the corresponding values ​​derived from the steady-state mode and the motion mode, where the steady-state mode derives the motion status of the human body, and the motion mode derives the estimated change of the human body based on the queue data;

[0018] Step 1-4, perform identification on the estimated changes in the movement pattern derived from the queue data through the critical quantity identification method.

[0019] Furthermore, in Step 1-1, the pre-processing of the steady-state values ​​is to extract parameters such as the height, weight, and three-dimensional curvature of the corresponding limbs when the human body starts moving. The pre-processing of the corresponding limb movement data of the human body is to arrange the respective queues of the three-dimensional curvature, angular velocity, and angular acceleration of the corresponding limbs of the human body in the order of their measurements.

[0020] Furthermore, in Step 1-2, the steady-state mode is constructed based on the existing parameters, which is the least squares method; the motion mode is constructed based on the queue data, which is the moving average mode.

[0021] Furthermore, Step 1-3 also includes: after the steady-state mode and the motion mode are constructed and the corresponding steady-state attribute values ​​and motion attribute values ​​are sent therein, the steady-state mode will derive the motion status of the human body;

[0022] The derived motion pattern will contain the estimated changes of the human body based on the queue data, that is, the estimated changes of the corresponding limb motion data of the human body based on the queue data. After obtaining the estimated changes of the corresponding limb motion data of the human body based on the queue data, the motion state of the human body can be estimated, so as to obtain the derived corresponding value of the same type as the steady-state mode.

[0023] Furthermore, in Step 1-4, the critical quantity identification method specifically includes:

[0024] Step 1-4-1, the controller obtains a motion parameter change value group of the human body motion, and performs decomposition on the motion parameter change value group;

[0025] Step 1-4-2, compare the estimated change value of the human body derived from the motion pattern according to the queue data with the input motion parameter change value group to obtain the comparison value;

[0026] Step 1-4-3, define the reduction threshold of the corresponding parameters, and identify the control value and the reduction threshold, and derive the human movement status with queue data.

[0027] Furthermore, in Step 1-4-2, the control method can be the value obtained by subtracting the input motion parameter change value group from the estimated value of the human body's change based on the queue data, and this value is the control value.

[0028] Furthermore, Step 2 also includes: removing the disturbance value, and the method for removing the disturbance value is: determining whether there is coherence between the steady-state value and the unreasonable data formed by the corresponding limb movement data of the human body in the processed data, if so, temporarily remove it, execute it first and then process it.

[0029] Furthermore, Step 2 also includes: determining the specific movement status of the human body based on the conclusion of the joint treatment, and the determination method includes:

[0030] Constructing a time point coordination mode, the time point coordination mode has a pair of feeding ends, where the pair of feeding ends respectively feed the derived corresponding value of the steady-state mode and the derived corresponding value of the motion mode;

[0031] The time point coordination mode can achieve time point coordination of different input sources, so that they carry data in the same order;

[0032] Define a constant correction period and perform repeated corrections within the correction period;

[0033] Performing detection of the coordination status of the time point coordination mode during the movement of the time point coordination mode;

[0034] After executing the time point coordination, the movement condition in which the corresponding value derived from the steady-state mode is the same as the corresponding value derived from the movement mode at the same reference time point is regarded as the movement condition of the human body.

[0035] A three-dimensional animation human body motion system, comprising:

[0036] The micro sensor unit is connected to a controller, and the controller is used to receive corresponding limb motion data of the human body measured by the micro sensor unit, and then process the corresponding limb motion data of the human body, and deduce the overall motion parameters of the human body according to the processed corresponding limb motion data of the human body, and finally drive the three-dimensional motion image of the human body according to the overall motion parameters of the human body, and reproduce the corresponding real person motion in the virtual world in the form of animation;

[0037] The modules running on the controller include:

[0038] A co-organizing module, which is used to collect the steady-state values ​​and the corresponding limb movement data of the human body during the human body movement, and perform co-organizing processing on the steady-state values ​​and the corresponding limb movement data of the human body after the collection is completed;

[0039] The identification module is used to remove unreasonable data after co-processing the steady-state values ​​and the corresponding limb movement data of the human body, and to identify the specific movement status of the human body;

[0040] The display module is used to transform the conclusion of the human body's movement status and transmit it to a liquid crystal screen connected to the controller for display.

[0041] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0042] By collecting the steady-state values ​​and the corresponding limb movement data of the human body during the human body movement, and performing coordinated processing on the steady-state values ​​and the corresponding limb movement data of the human body after the collection is completed, the human body's movement status is centrally identified based on the steady-state values ​​and the corresponding limb movement data of the human body, and the human body's movement status is transmitted to a liquid crystal screen connected to the controller for display, and a corresponding reference time point is also attached for post-detection maintenance; it is achieved to determine whether the measured corresponding limb movement data of the human body accurately reflects the corresponding human body movement status, that is, whether the micro-sensor unit fails and cannot make the measured corresponding limb movement data of the human body accurately reflect the corresponding human body movement status. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flow chart of a method for controlling a human body motion system of a three-dimensional animation in the present invention;

[0044] Figure 2 It is a partial structural diagram of the human body motion system of the three-dimensional animation described in the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention clearer, the following will be combined with the drawings in the embodiments of the present invention to clearly and completely express the technical solution of the present invention. The embodiments expressed in this application are only some embodiments of the present invention, not all embodiments. According to the spirit of the present invention, other embodiments obtained by technicians in this field without making creative work are all within the protection scope of the present invention.

[0046] like Figure 1 As shown, the control method of a human body motion system of a three-dimensional animation according to the present invention comprises:

[0047] The controller receives the corresponding limb motion data of the human body measured by the micro sensor unit, and then processes the corresponding limb motion data of the human body, and derives the overall motion parameters of the human body based on the processed corresponding limb motion data of the human body, and finally drives the three-dimensional motion image of the human body based on the overall motion parameters of the human body, and reproduces the corresponding real person motion in the virtual world in the form of animation;

[0048] A method for processing corresponding limb motion data of a human body, comprising:

[0049] Step 1, the controller collects the steady-state value and the corresponding limb movement data of the human body during the human body movement. The steady-state value can be entered into the controller in advance before the human body moves. The corresponding limb movement data of the human body is measured and transmitted by the micro sensor unit. After the collection is completed, the steady-state value and the corresponding limb movement data of the human body are processed in a coordinated manner;

[0050] In a preferred but non-limiting embodiment of the present invention, in Step 1, the corresponding limb motion data of the human body includes the three-dimensional radian, angular velocity, and angular acceleration of the corresponding limb of the human body.

[0051] In a preferred but non-limiting embodiment of the present invention, in Step 1, the steady-state values ​​include the height, weight, and three-dimensional curvature of the corresponding limbs of the human body when the human body starts to move.

[0052] Because the steady-state value and the corresponding limb movement data of the human body have different numerical attributes, their processing methods and calculation difficulties are somewhat different. In this application, the steady-state value and the corresponding limb movement data of the human body are also subjected to coordinated processing. In this application, coordinated processing is to process data of different categories (steady-state values ​​and corresponding limb movement data of the human body) to form data that can be processed in the same way and have the same calculation difficulty, so as to avoid errors in the analysis value caused by different methods for different categories. In a preferred but non-restrictive embodiment of the present invention, in Step 1, the method of co-processing the steady-state value and the corresponding limb movement data of the human body specifically includes:

[0053] Step 1-1, pre-processing the steady-state values ​​and the corresponding limb motion data of the human body to extract the steady-state attribute values ​​and motion attribute values;

[0054] Steady-state values ​​and the corresponding limb motion data of the human body often require different processing methods according to their different properties and application conditions. Such processing methods are not suitable for the application period of human body movement, so pre-processing is required. The pre-processing here is divided into pre-processing of steady-state values ​​and pre-processing of the corresponding limb motion data of the human body. In a preferred but non-restrictive implementation of the present invention, in Step 1-1, the pre-processing of the steady-state values ​​is to extract parameters such as the height, weight, and three-dimensional curvature of the corresponding limbs of the human body when the human body starts to move. The pre-processing of the corresponding limb motion data of the human body is to arrange the three-dimensional curvature, angular velocity, and angular acceleration of the corresponding limbs of the human body in the order of their measurements.

[0055] Step 1-2, respectively construct a steady-state model based on the existing parameters and a motion model based on the queue data, and send the extracted steady-state attribute values ​​and motion attribute values ​​into the corresponding models;

[0056] After the steady-state attribute values ​​and motion attribute values ​​are extracted, they need to be subjected to pattern processing. During the pattern processing, the coherence between different data is improved. Therefore, in the present application, aggregation processing is performed by constructing steady-state patterns and motion patterns. In a preferred but non-restrictive embodiment of the present invention, in Step 1-2, the steady-state pattern is constructed based on existing parameters, which is the least squares method; the motion pattern is constructed based on queue data, which is a moving average pattern. The above patterns have more than one value input terminal and value export terminal, and the value input terminal is used to input steady-state attribute values ​​and motion attribute values, and the value export terminal is used to export corresponding values ​​based on the input values.

[0057] Step 1-3, collecting the corresponding values ​​derived from the steady-state mode and the motion mode, where the steady-state mode derives the motion status of the human body, and the motion mode derives the estimated change of the human body based on the queue data;

[0058] In a preferred but non-limiting embodiment of the present invention, Step 1-3 also includes: after the steady-state mode and the motion mode are constructed and the corresponding steady-state attribute values ​​and motion attribute values ​​are sent therein, the steady-state mode will derive the motion state of the human body, that is, the comparison is performed based on the sent steady-state existing parameters and the reasonable motion state parameters of the human body, so as to identify the current motion state, and the motion state can be transformed into a bit value, just as the derived bit value of one is defined as reasonable human motion, and the derived bit value of zero is defined as unreasonable motion, and the human motion state is identified based on the derived corresponding value of the steady-state mode;

[0059] Because the motion pattern input is the motion attribute value, and the motion pattern is constructed based on the queue data, the derived motion pattern will contain the estimated change of the human body based on the queue data, that is, the estimated change of the corresponding limb motion data of the human body based on the queue data. After obtaining the estimated change value of the corresponding limb motion data of the human body based on the queue data, the motion state of the human body can be estimated, so as to obtain the derived corresponding value of the same attribute as the steady-state pattern (that is, the motion state of the human body).

[0060] Step 1-4, perform identification on the estimated changes in the movement pattern derived from the queue data through the critical quantity identification method.

[0061] When a person exercises, his or her limbs will be measured and a motion parameter change value group with queue data will be formed. Under current application conditions, the motion parameter change value group can only be used during human exercise. After the person exercises, the queue data can only be obtained through a constant motion pattern, and then the above motion parameter change value group can be used for comparison. In the present application, the change estimate based on the queue data derived from the motion pattern satisfies the classification of the corresponding limb motion data of the human body, so the motion parameter change value group can be used to identify the motion status of the human body at each moment in the queue data through the critical quantity identification method.

[0062] In a preferred but non-limiting embodiment of the present invention, in Step 1-4, the critical quantity identification method specifically includes:

[0063] Step 1-4-1, the controller obtains a motion parameter change value group of the human body motion, and performs decomposition on the motion parameter change value group;

[0064] The group of change values ​​of motion parameters of human body motion is decomposed to make the parameters of each category independent and convenient for subsequent comparison.

[0065] Step 1-4-2, compare the estimated change value of the human body derived from the motion pattern according to the queue data with the input motion parameter change value group to obtain the comparison value;

[0066] In a preferred but non-limiting embodiment of the present invention, in Step 1-4-2, the control method can be the value obtained by subtracting the input motion parameter change value group from the estimated value of the human body's change based on the queue data, and this value is the control value.

[0067] Step 1-4-3, define the reduction threshold of the corresponding parameters, and identify the control value and the reduction threshold, and derive the human movement status with queue data.

[0068] After defining the critical value of the corresponding parameter reduction, the control value in Step 1-4-2 and the above critical value are identified. When one or more motion parameters are higher than the defined critical value, the human body movement is determined to be unreasonable. When all motion parameters are lower than the defined critical value, the human body movement is determined to be reasonable. After the identification is completed, the identification conclusion is derived and made to be the same as the derived corresponding value of the steady-state mode.

[0069] Step 2, after co-processing the steady-state values ​​and the corresponding limb movement data of the human body, the unreasonable data is removed, and the specific movement status of the human body is identified;

[0070] In a preferred but non-restrictive implementation of the present invention, Step 2 also includes: after the coordinated processing of the steady-state values ​​and the corresponding limb motion data of the human body is completed, disturbances may occur from time to time between the steady-state corresponding limb motion data of the human body. When analyzing after execution, the disturbance value must be removed, and the method for removing the disturbance value is: determine whether there is coherence between the unreasonable data formed by the steady-state values ​​and the corresponding limb motion data of the human body in the processed data (the naive Bayes algorithm can be used to obtain whether there is coherence between the unreasonable data formed by the steady-state values ​​and the corresponding limb motion data of the human body). If so, temporarily remove it, execute it first and then process it. Just as the three-dimensional curvature of the corresponding limb of the steady-state value and the angular velocity of the corresponding limb of the corresponding limb motion data of the human body are not coordinated reasonably, it can be directly determined that the angular velocity of the corresponding limb of the human body motion is unreasonable, and the above data is temporarily removed, and the remaining data is processed to determine other unreasonable motion data.

[0071] The steady-state mode and the motion mode respectively derive the human body motion status under the steady-state value and the human body motion status under the corresponding limb motion data of the human body. In specific applications, the steady-state value and the corresponding limb motion data of the human body are coordinated and executed, so they should also correspond to the same motion status. In a preferred but non-limiting embodiment of the present invention, Step 2 also includes: Therefore, the specific motion status of the human body must be identified based on the co-organized treatment conclusion, and the identification method includes:

[0072] Constructing a time point coordination mode, the time point coordination mode has a pair of feeding ends, where the pair of feeding ends respectively feed the derived corresponding value of the steady-state mode and the derived corresponding value of the motion mode;

[0073] The time point coordination mode can achieve the time point coordination of different input sources, so that they have the same order of data. Because the steady-state value often does not have the data in the order of sequence, after the steady-state value is input into the time point coordination mode, the steady-state value will be given the data in the order of sequence. Here, the time point coordination mode is the B code time calibration method. The time point coordination mode is coordinated and corrected, so that the steady-state mode and the motion mode perform data collection and data export based on the same reference time point;

[0074] When using the time point coordination mode, coordination correction is necessary, because the derived response value of the motion mode itself has data in a certain order, which may collide with the reference time point defined by the time point coordination mode from time to time, so coordination correction must be performed on the time point coordination mode to make it the same as the reference time point;

[0075] Define a constant correction period and perform repeated corrections within the correction period;

[0076] To achieve active correction, a constant correction period can also be defined. During the constant correction period, coordination correction is performed on the time point coordination mode. In this application, the correction period can be defined as 60 minutes. The correction method of exercise frequency can also be used. After each constant frequency of human body movement, a coordination correction is performed.

[0077] Performing detection of the coordination status of the time point coordination mode during the movement of the time point coordination mode;

[0078] During the movement of the time point coordination mode, the coordination status of the time point coordination mode is detected, and when the data of the derived corresponding value of the corresponding limb movement data of the human body collides with the reference time point defined by the time point coordination mode, a correction is actively activated.

[0079] After executing the time point coordination, the movement condition in which the corresponding value derived from the steady-state mode is the same as the corresponding value derived from the movement mode at the same reference time point is regarded as the movement condition of the human body.

[0080] Just as, after time point coordination, at the same reference time point, the derived corresponding value of the steady-state mode is bit value one, and the derived corresponding value of the motion mode is also bit value one, it can be determined that the human body movement is reasonable. At the same reference time point, if the derived corresponding value of any mode is bit value zero, it can be determined that the human body movement is unreasonable.

[0081] Step 3, transform the conclusion of the human body's movement status and transmit it to the LCD screen connected to the controller for display.

[0082] After obtaining the recognition conclusion, it must be transformed and transmitted to the LCD screen connected to the controller for display. Just as the recognition conclusion is transformed into text and transmitted to the LCD screen, the LCD screen will display "the microsensor unit fails and cannot allow the corresponding limb movement data of the human body measured by it to accurately reflect the corresponding human body movement status" based on the recognition conclusion that the human body movement is unreasonable, or "the microsensor unit is fine and the corresponding limb movement data of the human body measured by it accurately reflects the corresponding human body movement status" based on the recognition conclusion that the human body movement is reasonable, and the reference time point information of the current time point coordination mode is attached for subsequent maintenance.

[0083] like Figure 2 As shown, the human body motion system of three-dimensional animation described in the present invention comprises:

[0084] The micro sensor unit is connected to a controller, and the controller is used to receive corresponding limb motion data of the human body measured by the micro sensor unit, and then process the corresponding limb motion data of the human body, and deduce the overall motion parameters of the human body according to the processed corresponding limb motion data of the human body, and finally drive the three-dimensional motion image of the human body according to the overall motion parameters of the human body, and reproduce the corresponding real person motion in the virtual world in the form of animation;

[0085] The modules running on the controller include:

[0086] A co-organizing module, which is used to collect the steady-state values ​​and the corresponding limb movement data of the human body during the human body movement, and perform co-organizing processing on the steady-state values ​​and the corresponding limb movement data of the human body after the collection is completed;

[0087] The identification module is used to remove unreasonable data after co-processing the steady-state values ​​and the corresponding limb movement data of the human body, and to identify the specific movement status of the human body;

[0088] The display module is used to transform the conclusion of the human body's movement status and transmit it to a liquid crystal screen connected to the controller for display.

[0089] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0090] By collecting the steady-state values ​​and the corresponding limb movement data of the human body during the human body movement, and performing coordinated processing on the steady-state values ​​and the corresponding limb movement data of the human body after the collection is completed, the human body's movement status is centrally identified based on the steady-state values ​​and the corresponding limb movement data of the human body, and the human body's movement status is transmitted to a liquid crystal screen connected to the controller for display, and a corresponding reference time point is also attached for post-detection maintenance; it is achieved to determine whether the measured corresponding limb movement data of the human body accurately reflects the corresponding human body movement status, that is, whether the micro-sensor unit fails and cannot make the measured corresponding limb movement data of the human body accurately reflect the corresponding human body movement status.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the protection space of the claims of the present invention.

Claims

1. A method for controlling a human motion system of a three-dimensional animation, characterized in that: include: The controller receives the corresponding limb motion data of the human body measured by the micro sensor unit, and then processes the corresponding limb motion data of the human body, and derives the overall motion parameters of the human body based on the processed corresponding limb motion data of the human body, and finally drives the three-dimensional motion image of the human body based on the overall motion parameters of the human body, and reproduces the corresponding real person motion in the virtual world in the form of animation; A method for processing corresponding limb motion data of a human body, comprising: Step 1, the controller collects the steady-state values ​​and the corresponding limb movement data of the human body during the human body movement, and performs coordinated processing on the steady-state values ​​and the corresponding limb movement data of the human body after the collection is completed; Step 2, after co-processing the steady-state values ​​and the corresponding limb movement data of the human body, the unreasonable data is removed, and the specific movement status of the human body is identified; Step 3, transform the conclusion of the human body's movement status and transmit it to the LCD screen connected to the controller for display.

2. The control method of the human body motion system of three-dimensional animation according to claim 1, characterized in that: In Step 1, the corresponding limb motion data of the human body includes the three-dimensional arc, angular velocity, and angular acceleration of the corresponding limb of the human body; In Step 1, the steady-state values ​​include the height, weight, and three-dimensional arc of the corresponding limbs when the human body starts to move.

3. The control method of the human body motion system of three-dimensional animation according to claim 2, characterized in that: In Step 1, the method of co-processing the steady-state value and the corresponding limb movement data of the human body includes: Step 1-1, pre-processing the steady-state values ​​and the corresponding limb motion data of the human body to extract the steady-state attribute values ​​and motion attribute values; Step 1-2, respectively construct a steady-state model based on the existing parameters and a motion model based on the queue data, and send the extracted steady-state attribute values ​​and motion attribute values ​​into the corresponding models; Step 1-3, collecting the corresponding values ​​derived from the steady-state mode and the motion mode, where the steady-state mode derives the motion status of the human body, and the motion mode derives the estimated change of the human body based on the queue data; Step 1-4, perform identification on the estimated changes in the movement pattern derived from the queue data through the critical quantity identification method.

4. The method for controlling the human body motion system of three-dimensional animation according to claim 3, characterized in that: In Step 1-1, the pre-processing of the steady-state values ​​is to extract parameters such as the height, weight, and three-dimensional curvature of the corresponding limbs when the human body starts to move. The pre-processing of the corresponding limb movement data of the human body is to arrange the three-dimensional curvature, angular velocity, and angular acceleration of the corresponding limbs of the human body in the order of their measurements.

5. The method for controlling the human body motion system of three-dimensional animation according to claim 4, characterized in that: In Step 1-2, the steady-state mode is constructed based on the existing parameters, which is the least squares method; the motion mode is constructed based on the queue data, which is the moving average mode.

6. The method for controlling the human body motion system of three-dimensional animation according to claim 5, characterized in that: Step 1-3 also includes: after the steady-state mode and the motion mode are constructed and the corresponding steady-state attribute values ​​and motion attribute values ​​are sent into them, the steady-state mode will derive the motion status of the human body; The derived motion pattern will contain the estimated changes of the human body based on the queue data, that is, the estimated changes of the corresponding limb motion data of the human body based on the queue data. After obtaining the estimated changes of the corresponding limb motion data of the human body based on the queue data, the motion state of the human body can be estimated, so as to obtain the derived corresponding value of the same type as the steady-state mode.

7. The method for controlling the human body motion system of three-dimensional animation according to claim 6, characterized in that: In Step 1-4, the critical quantity identification method specifically includes: Step 1-4-1, the controller obtains a motion parameter change value group of the human body motion, and performs decomposition on the motion parameter change value group; Step 1-4-2, compare the estimated change value of the human body derived from the motion pattern according to the queue data with the input motion parameter change value group to obtain the comparison value; Step 1-4-3, define the reduction threshold of the corresponding parameters, and identify the control value and the reduction threshold, and derive the human movement status with queue data.

8. The method for controlling the human body motion system of three-dimensional animation according to claim 7, characterized in that: In Step 1-4-2, the control method can be the value obtained by subtracting the input motion parameter change value group from the estimated value of the human body change based on the queue data, and this value is the control value.

9. The method for controlling the human body motion system of three-dimensional animation according to claim 8, characterized in that: Step 2 also includes: removing the disturbance value, and the method of removing the disturbance value is: determining whether there is a correlation between the steady-state value and the unreasonable data formed by the corresponding limb movement data of the human body in the processed data, and if so, temporarily removing it, executing it first and then processing it; Step 2 also includes: according to the conclusion of the joint treatment, the specific movement status of the human body is identified, and the identification method includes: Constructing a time point coordination mode, the time point coordination mode has a pair of feeding ends, where the pair of feeding ends respectively feed the derived corresponding value of the steady-state mode and the derived corresponding value of the motion mode; The time point coordination mode can achieve time point coordination of different input sources, so that they carry data in the same order; Define a constant correction period and perform repeated corrections within the correction period; Performing detection of the coordination status of the time point coordination mode during the movement of the time point coordination mode; After executing the time point coordination, the movement condition in which the corresponding value derived from the steady-state mode is the same as the corresponding value derived from the movement mode at the same reference time point is regarded as the movement condition of the human body.

10. A three-dimensional animation human body motion system, characterized in that: include: The micro sensor unit is connected to a controller, and the controller is used to receive corresponding limb motion data of the human body measured by the micro sensor unit, and then process the corresponding limb motion data of the human body, and deduce the overall motion parameters of the human body according to the processed corresponding limb motion data of the human body, and finally drive the three-dimensional motion image of the human body according to the overall motion parameters of the human body, and reproduce the corresponding real person motion in the virtual world in the form of animation; The modules running on the controller include: A co-organizing module, which is used to collect the steady-state values ​​and the corresponding limb movement data of the human body during the human body movement, and perform co-organizing processing on the steady-state values ​​and the corresponding limb movement data of the human body after the collection is completed; The identification module is used to remove unreasonable data after co-processing the steady-state values ​​and the corresponding limb movement data of the human body, and to identify the specific movement status of the human body; The display module is used to transform the conclusion of the human body's movement status and transmit it to a liquid crystal screen connected to the controller for display.

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