Children wearing assisting method and system based on AR technology

Abstract

The invention discloses a child wearing assisting method and system based on the AR technology, and relates to the technical field of virtual reality, the system comprises a management center, and the management center is connected with a display acquisition module, an enhanced processing module, an aided design module and a wearing detection module; constructing an attribute interaction matrix, screening and matching the wearing capture data to obtain matching auxiliary steps, extracting and converting the matching auxiliary steps to obtain an initial activity coefficient, and performing deformation updating on the attribute interaction matrix through the initial activity coefficient to obtain an initial attribute matrix; performing element replacement on the initial attribute matrix to obtain a deformation attribute matrix, and performing action feature capture on the standard wearing capture graph through the deformation attribute matrix to obtain a wearing feature graph; generating a wearing feature sequence according to the wearing feature pattern, and performing intelligent prediction assistance on the target user through the wearing feature sequence; the recognition precision is greatly improved, and the interaction experience is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality technology, and in particular to a children's wearing assistance method and system based on AR technology. Background Art

[0002] At present, there are some auxiliary products for children to wear on the market, such as clothing with patterns or logos, wearing instructions, etc. However, these products generally have problems such as poor interactivity and lack of fun, which makes it difficult to effectively attract children's attention and unable to provide personalized wearing guidance according to the actual situation of children.

[0003] With the rapid development of augmented reality (AR) technology, it is not only increasingly used in education, entertainment and other fields, but also in the field of children's wear, it can also greatly improve the problems of low efficiency and discomfort in traditional wearing methods. By superimposing virtual information on the real world, AR technology can intuitively display the wearing steps, provide real-time guidance, and increase the fun of the wearing process, thereby effectively improving the efficiency and comfort of children's wearing. To this end, a children's wearing assistance method and system based on AR technology are provided. Summary of the invention

[0004] The purpose of the present invention is to provide a children's wearing assistance method and system based on AR technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A children's wearing assistance system based on AR technology includes a management center, wherein the management center is connected to a display acquisition module, an enhanced processing module, an auxiliary design module, and a wearing detection module;

[0007] The display acquisition module is used to collect wearable capture data;

[0008] The enhanced processing module is used to construct an attribute interaction matrix, screen and match the wearable capture data to obtain matching auxiliary steps, extract and transform the matching auxiliary steps to obtain initial activity coefficients, and deform and update the attribute interaction matrix through the initial activity coefficients to obtain an initial attribute matrix;

[0009] The auxiliary design module is used to replace elements of the initial attribute matrix to obtain a deformation attribute matrix, and to capture motion features of the standard wear capture image through the deformation attribute matrix to obtain a wear feature image;

[0010] The wearing detection module is used to generate a wearing feature sequence according to the wearing feature graph, and to assist in intelligent prediction of the target user through the wearing feature sequence.

[0011] Preferably, the process of the display acquisition module acquiring wearable capture data includes:

[0012] Collect information from wearable assistive devices to obtain target assistive steps;

[0013] Collect actions of wearable assistive devices and obtain execution response instructions;

[0014] Start monitoring the wearable assistive device according to the execution response instruction, obtain the application assistive device, upload the obtained target assistive steps to the application assistive device, and issue a preparatory operation instruction to the target user according to the obtained application assistive device based on the target assistive steps;

[0015] The target user performs wear-based execution according to the received preparatory operation instructions, and uses auxiliary equipment to capture and capture the wear-based execution process to obtain wear-based capture data.

[0016] Preferably, the process of screening and matching the wearable captured data includes:

[0017] Set a capture standard, perform standard screening on the wearable capture data according to the capture standard, and obtain a standard wearable capture image;

[0018] Setting an attribute interaction matrix for the obtained standard wearable capture image;

[0019] Action matching is performed on the standard wearable capture image according to the obtained target auxiliary step to obtain a matching auxiliary step.

[0020] Preferably, the process of extracting and converting the matching auxiliary step includes:

[0021] Perform screening transformation on the matching auxiliary steps to obtain the target step signal;

[0022] Perform element design on the attribute interaction matrix to obtain conversion extraction coefficients;

[0023] The target step signal is compared and extracted according to the conversion extraction coefficient to obtain the initial activity coefficient.

[0024] Preferably, the process of performing deformation updating on the attribute interaction matrix through the initial activity coefficient includes:

[0025] Performing deformation transformation on the obtained initial activity coefficient to obtain shape parameters;

[0026] According to the obtained shape parameters, the initial activity coefficient is subjected to margin statistics to obtain the deformation interval;

[0027] The deformation number is obtained according to the obtained shape parameters and deformation interval, and the attribute interaction matrix is ​​initialized according to the deformation number to obtain the initial attribute matrix.

[0028] Preferably, the process of the auxiliary design module replacing elements of the initial attribute matrix includes:

[0029] Obtain the deformation number, segment and collect the initial activity coefficient according to the deformation number, and obtain the initial deformation coefficient segment;

[0030] The initial attribute matrix is ​​initially replaced according to the obtained initial deformation coefficient segment to obtain the deformation attribute matrix.

[0031] Preferably, the process of capturing motion features of the standard wearable capture image through the deformation attribute matrix includes:

[0032] Upload the deformation attribute matrix to the starting point of the standard wearable capture image to obtain the attribute screening area;

[0033] The attribute screening area is extracted within the area through the deformation attribute matrix to obtain the attribute extraction block;

[0034] A smoothing interval is set for the deformation attribute matrix, and the deformation attribute matrix is ​​translated and slid based on the smoothing interval to reach the next attribute screening area, and the area is extracted with the attribute screening area until the cutoff point of the standard wearable capture image is reached;

[0035] Based on the standard wear capture graph, the attribute extraction blocks are combined to obtain the wear feature graph.

[0036] Preferably, the process of performing intelligent prediction assistance on the target user through the wearing feature sequence includes:

[0037] Obtaining a wearing feature graph, and sorting the wearing feature graph based on the target auxiliary step to obtain a wearing feature sequence;

[0038] Upload the wearing feature sequence to the wearing auxiliary device, and use the wearing auxiliary device for auxiliary display to obtain the target wearing path;

[0039] Based on the wearing auxiliary device, the target user is matched and positioned according to the target wearing path to obtain the user's wearing stage;

[0040] According to the target wearing path, real-time prediction assistance is performed on the obtained user wearing stage until the target user completes the target wearing path.

[0041] Based on the above-mentioned child wearing assistance system based on AR technology, the present invention also provides a child wearing assistance method based on AR technology, comprising the following steps:

[0042] Step 1: Collect wearable capture data;

[0043] Step 2: Construct an attribute interaction matrix, screen and match the wearable capture data, obtain matching auxiliary steps, extract and transform the matching auxiliary steps, obtain the initial activity coefficient, and deform and update the attribute interaction matrix through the initial activity coefficient to obtain the initial attribute matrix;

[0044] Step 3: Replace the elements of the initial attribute matrix to obtain a deformation attribute matrix, and use the deformation attribute matrix to capture the motion features of the standard wearable capture image to obtain a wearable feature image;

[0045] Step 4: Generate a wearing feature sequence based on the wearing feature graph, and use the wearing feature sequence to assist in intelligent prediction of the target user.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. Collect image information during user use through wearable assistive devices, construct an attribute interaction matrix for deformation update, obtain an initial attribute matrix, replace elements of the initial attribute matrix, and obtain a deformation attribute matrix; combine the actual auxiliary steps with the feature extraction coefficient, which is conducive to improving the accuracy of feature extraction and the accuracy of auxiliary information;

[0048] 2. The motion features of the standard wear capture image are captured through the deformation attribute matrix to obtain the wear feature map, and the wear feature sequence is generated according to the wear feature map. The target user is intelligently predicted and assisted through the wear feature sequence; the feature matrix is ​​used to collect features of the image to obtain the feature map, which is conducive to simplifying the wearing process, visually displaying the wearing steps and wearing order, improving the accuracy of children's wearing, optimizing the interactive experience, and enhancing the degree of personalized assistance. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0051] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] like Figure 1 As shown, the child wearing assistance system based on AR technology includes a management center, which is connected to a display acquisition module, an enhanced processing module, an auxiliary design module and a wearing detection module;

[0053] The display acquisition module is used to collect wearable capture data;

[0054] The enhanced processing module is used to construct an attribute interaction matrix, screen and match the wearable capture data to obtain matching auxiliary steps, extract and transform the matching auxiliary steps to obtain initial activity coefficients, and deform and update the attribute interaction matrix through the initial activity coefficients to obtain an initial attribute matrix;

[0055] The auxiliary design module is used to replace elements of the initial attribute matrix to obtain a deformation attribute matrix, and to capture motion features of the standard wear capture image through the deformation attribute matrix to obtain a wear feature image;

[0056] The wearing detection module is used to generate a wearing feature sequence according to the wearing feature graph, and to perform intelligent prediction assistance for the target user through the wearing feature sequence.

[0057] In actual use, the process of the display acquisition module collecting wearable capture data includes:

[0058] Collect information from wearable assistive devices to obtain target assistive steps;

[0059] The wearing assistance device refers to a device provided to children for assisting operations during the wearing process, and the target assistance step refers to a specific wearing step corresponding to the wearing assistance content. For example, for children's rehabilitation assistance devices, the target assistance step is a specific action operation used to assist children in completing the required action, that is, the wearing assistance device can be used to assist children in completing or enhancing the required operation according to the obtained target assistance step;

[0060] Collect actions of wearable assistive devices and obtain execution response instructions;

[0061] The action collection means collecting all instruction information of the wearing assistive device to obtain an execution response instruction, wherein the instruction information represents a start assistive instruction, a stop assistive instruction, a standby instruction, and a pause assistive instruction of the wearing assistive device;

[0062] Start monitoring the wearable assistive device according to the obtained execution response instruction, obtain the application assistive device, upload the obtained target assistive step to the application assistive device, and issue a preparatory operation instruction to the target user according to the obtained application assistive device based on the target assistive step;

[0063] The start monitoring means starting the wearing assistance device according to the start assistance instruction in the obtained execution response instruction, and obtaining the application assistance device, which means that the wearing assistance device at this time can monitor the behavior of the target user, that is, assist the wearing operation of the target user, wherein the target user means the user who uses the wearing assistance device, and in this embodiment, the target user is a child; the preparatory operation instruction means that the application assistance device has been started and is ready to monitor the wearing behavior of the target user, that is, notifies the target user that the application assistance device can wear the device at any time; in particular, the application assistance device monitors the behavior of the target user according to the uploaded target assistance step, and detects whether the wearing behavior of the target user is correct through the target assistance step, and corrects and guides the incorrect behavior;

[0064] The target user performs wearing according to the received preparatory operation instructions, and uses auxiliary equipment to capture and collect the wearing execution process to obtain wearing capture data;

[0065] The wearing execution indicates that the target user performs a wearing operation. During the operation, an auxiliary device is used to collect real-time data, that is, images of the target user during the wearing operation are captured, and the image is collected through a camera to obtain wearing capture data, that is, the wearing capture data is expressed in the form of images.

[0066] The enhanced processing module is used to construct an attribute interaction matrix, screen and match the wearable capture data, obtain matching auxiliary steps, extract and transform the matching auxiliary steps, obtain initial activity coefficients, and deform and update the attribute interaction matrix through the initial activity coefficients to obtain an initial attribute matrix. The specific process includes:

[0067] Setting a capture standard, wherein the capture standard includes a length dimension, a width dimension, and a channel element, wherein the length dimension represents the number of pixels of the image in the horizontal direction, the width dimension represents the number of pixels of the image in the vertical direction, and the channel element represents the number of colors allowed to pass through the image, and each color represents a channel element;

[0068] Performing standard screening on the wearable capture data according to the obtained capture standard to obtain a standard wearable capture image;

[0069] The standard screening means unifying the pixels of each image in the wearable capture data according to the length and width dimensions in the capture standard, that is, limiting the number of pixels in the horizontal and vertical directions of the image, and then standardizing the color of the image in combination with the channel element to obtain a standard wearable capture image with unified pixels and color range;

[0070] An attribute interaction matrix is ​​set for the obtained standard wearable capture image, wherein the attribute interaction matrix includes a matrix length and a matrix width, wherein the matrix length represents the length dimension occupied by the attribute interaction matrix in the image, and the matrix width represents the width dimension occupied by the attribute interaction matrix in the image, and the size occupied by the attribute interaction matrix in the image is determined according to the length dimension and the width dimension;

[0071] Furthermore, the attribute interaction matrix is ​​a matrix block uploaded to the standard wearable capture image and used for translation and sliding in the standard wearable capture image. The matrix block occupies a part of the image of the standard wearable capture image, and the length of the part of the image occupied represents the matrix length, and the width of the part of the image occupied represents the matrix width;

[0072] Performing action matching on the standard wearable capture image according to the obtained target auxiliary step to obtain a matching auxiliary step, and associating the obtained matching auxiliary step with the corresponding standard wearable auxiliary capture image;

[0073] The action matching means filtering out relevant step contents in the target auxiliary step according to the standard wearable capture image, and recording the relevant step contents as matching auxiliary steps, that is, standard step content data of the standard wearable capture image;

[0074] Performing screening conversion on the obtained matching auxiliary steps to obtain a target step signal, wherein the screening conversion means converting the obtained matching auxiliary steps into a signal form;

[0075] Performing element design on the obtained attribute interaction matrix to obtain a conversion extraction coefficient, wherein the conversion extraction coefficient is expressed in a function form;

[0076] Comparing and extracting the target step signal according to the obtained conversion extraction coefficient to obtain the initial activity coefficient, wherein the comparing and extracting means multiplying the obtained target step signal with the initial activity coefficient to obtain the initial activity coefficient;

[0077] Performing deformation transformation on the obtained initial activity coefficient to obtain shape parameters, wherein the deformation transformation means controlling the initial activity coefficient to perform scaling and translation transformation in the time dimension and the frequency dimension, and performing statistics on the distance of the scaling and translation transformation to obtain the shape parameters;

[0078] According to the obtained shape parameters, the initial activity coefficient is subjected to margin statistics to obtain the deformation interval;

[0079] The process of margin statistics includes:

[0080] The distance between two adjacent shape parameters is counted in the initial activity coefficient to obtain the parameter spacing. The parameter spacing is counted based on the initial activity coefficient to obtain the spacing number. The deformation interval is obtained according to the obtained spacing number and parameter spacing, and the obtained deformation interval is marked as BG, where: i represents the number of parameter intervals, C i represents the parameter spacing, s represents the number of spacings, i=1, 2, 3, ..., v1, v1 is a positive integer;

[0081] The deformation number is obtained according to the obtained shape parameters and deformation interval, and the obtained deformation number is marked as Z, where: L represents the coefficient length of the initial activity coefficient, and m represents the shape parameter;

[0082] The attribute interaction matrix is ​​initialized according to the obtained number of deformations to obtain an initial attribute matrix. The element initialization means setting the elements in the attribute interaction matrix according to the number of deformations, and initializing the elements of the attribute interaction matrix into a matrix of k rows and k columns according to the number of deformations, wherein k 2 ≥Z, and fill the redundant element positions with zeros. The "redundant element positions" represent the part where the number of elements exceeds the number of deformations after the attribute interaction matrix is ​​initialized.

[0083] The auxiliary design module is used to replace elements of the initial attribute matrix to obtain a deformation attribute matrix, and to capture motion features of the standard wear capture image through the deformation attribute matrix to obtain a wear feature image. The specific process includes:

[0084] Obtain the deformation number, segment and collect the initial activity coefficient according to the deformation number, and obtain the initial deformation coefficient segment;

[0085] The segmentation acquisition means that the initial activity coefficient is equally divided into a corresponding number of initial deformation coefficient segments according to the number of deformations, that is, the number of initial deformation coefficient segments is equal to the number of deformations, and the length of each initial deformation coefficient segment is equal;

[0086] Performing initial replacement on the initial attribute matrix according to the obtained initial deformation coefficient segment to obtain a deformation attribute matrix;

[0087] The initial replacement marker uploads the obtained initial deformation coefficient segments to the initial attribute matrix based on the order of segmentation and acquisition, and replaces the elements at the original positions to obtain the deformation attribute matrix, and the replacement is performed in the order of each row from left to right;

[0088] The obtained deformation attribute matrix is ​​uploaded to the standard wearable capture image, and the motion feature of the standard wearable capture image is captured by the deformation attribute matrix to obtain a wearable feature image;

[0089] It should be further explained that, in the specific implementation process, the process of capturing the motion features includes:

[0090] The obtained deformation attribute matrix is ​​uploaded to the starting point of the standard wearable capture image, and the overlapping area of ​​the deformation attribute matrix and the standard wearable capture image is recorded as the attribute screening area, wherein the starting point represents the initial position of the deformation attribute matrix in the standard wearable capture image, that is, the position where the movement starts;

[0091] The attribute screening area is extracted within the area through the deformation attribute matrix to obtain the attribute extraction block;

[0092] The intra-region extraction means convolving the elements in the deformation attribute matrix with the pixels at corresponding positions in the attribute screening region to obtain the attribute screening block;

[0093] Setting a smoothing interval for the obtained deformation attribute matrix, where the smoothing interval represents the distance for moving the deformation attribute matrix to the next attribute screening area in the standard wear capture image;

[0094] Based on the smoothing interval, the obtained deformation attribute matrix is ​​translated and slid to reach the next attribute screening area, and the area extraction is performed with the attribute screening area until the cutoff point of the standard wear capture image is reached to obtain the attribute extraction block, wherein the cutoff point represents the end point of the translation sliding set at the corresponding starting point, that is, when reaching this point, the deformation attribute matrix does not need to be translated and slid any more;

[0095] Based on the standard wear capture image, attributes of the obtained attribute extraction blocks are combined to obtain a wear feature image;

[0096] The attribute combination means collecting the attribute extraction blocks according to the order of translation and sliding, and combining the collected attribute extraction blocks with the standard wear capture map to obtain the wear feature map.

[0097] The wearing detection module is used to generate a wearing feature sequence according to the wearing feature graph, and to perform intelligent prediction assistance on the target user through the wearing feature sequence. The specific steps include:

[0098] Obtaining a wearing feature graph, and sorting the wearing feature graph based on the target auxiliary step to obtain a wearing feature sequence;

[0099] The step sorting means that the matching auxiliary steps are sorted according to the order of the target auxiliary steps and the matching auxiliary steps associated with the wearing feature graph, and the sorting corresponding to the wearing feature graph is obtained, which is the wearing feature sequence; the wearing feature sequence represents the image sequence steps of the standard wearing steps of the target user using the wearing auxiliary device, and the next wearing step can be intuitively observed through the image sequence;

[0100] The acquired wearing feature sequence is uploaded to a wearing auxiliary device, and the wearing auxiliary device is used for auxiliary display to obtain a target wearing path;

[0101] The auxiliary display means uploading all feature images of the wearing feature sequence to the wearing auxiliary device in order for image display, so that the target user can directly obtain the next wearing step;

[0102] Based on the wearing auxiliary device, the target user is matched and positioned according to the obtained target wearing path to obtain the user wearing stage;

[0103] The matching positioning means matching the wearing action corresponding to the target task at the current moment according to the displayed target wearing path, that is, the user wearing stage;

[0104] According to the obtained target wearing path, real-time prediction assistance is performed on the obtained user wearing stage until the target user completes the target wearing path, and the wearing assistance device that completes the target wearing path is recorded as the assistance completion stage;

[0105] The wearable assistive device is virtually guarded according to the obtained execution response instruction until the standby end is reached, and an execution response instruction is issued to the wearable assistive device, thereby completing the assistive wearing;

[0106] It should be further explained that, in the specific implementation process, the real-time prediction assistance means assisting the next step of the user's wearing stage, and assisting the target user's action according to the wearing feature map corresponding to the next matching assistance step. For example, according to the display of the wearing feature map, the target user is assisted in adjusting the dressing process by the wearing assistance device, such as pushing the sleeves, pulling the trouser legs, etc.;

[0107] The virtual guarding means starting the standby command after completing the target wearing path, guarding the target user during the standby process, and if the target user still does not move when the standby end is reached, the termination assistance command is started by executing the response command, the wearing assistance device is turned off, and the current assistance operation is completed.

[0108] Based on the above-mentioned child wearing assistance system based on AR technology, the present invention also provides a child wearing assistance method based on AR technology, comprising the following steps:

[0109] Step 1: Collect wearable capture data;

[0110] Step 2: Construct an attribute interaction matrix, screen and match the wearable capture data, obtain matching auxiliary steps, extract and transform the matching auxiliary steps, obtain the initial activity coefficient, and deform and update the attribute interaction matrix through the initial activity coefficient to obtain the initial attribute matrix;

[0111] Step 3: Replace the elements of the initial attribute matrix to obtain a deformation attribute matrix, and use the deformation attribute matrix to capture the motion features of the standard wearable capture image to obtain a wearable feature image;

[0112] Step 4: Generate a wearing feature sequence based on the wearing feature graph, and use the wearing feature sequence to assist in intelligent prediction of the target user.

[0113] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A children's wear assistance system based on AR technology, including a management center, characterized in that: The management center is connected to a display acquisition module, an enhanced processing module, an auxiliary design module and a wear detection module; The display acquisition module is used to collect wearable capture data; The enhanced processing module is used to construct an attribute interaction matrix, screen and match the wearable capture data to obtain matching auxiliary steps, extract and transform the matching auxiliary steps to obtain initial activity coefficients, and deform and update the attribute interaction matrix through the initial activity coefficients to obtain an initial attribute matrix; The auxiliary design module is used to replace elements of the initial attribute matrix to obtain a deformation attribute matrix, and to capture motion features of the standard wear capture image through the deformation attribute matrix to obtain a wear feature image; The wearing detection module is used to generate a wearing feature sequence according to the wearing feature graph, and to assist in intelligent prediction of the target user through the wearing feature sequence.

2. The AR technology-based children's wearable assistance system according to claim 1, characterized in that: The process of the display acquisition module acquiring wearable capture data includes: Collect information from wearable assistive devices to obtain target assistive steps; Collect actions of wearable assistive devices and obtain execution response instructions; Start monitoring the wearable assistive device according to the execution response instruction, obtain the application assistive device, upload the obtained target assistive steps to the application assistive device, and issue a preparatory operation instruction to the target user according to the obtained application assistive device based on the target assistive steps; The target user performs wear-based execution according to the received preparatory operation instructions, and uses auxiliary equipment to capture and capture the wear-based execution process to obtain wear-based capture data.

3. The AR technology-based children's wearable assistance system according to claim 2, characterized in that: The process of screening and matching wearable captured data includes: Set a capture standard, perform standard screening on the wearable capture data according to the capture standard, and obtain a standard wearable capture image; Setting an attribute interaction matrix for the obtained standard wearable capture image; Action matching is performed on the standard wearable capture image according to the obtained target auxiliary step to obtain a matching auxiliary step.

4. The AR technology-based children's wearable assistance system according to claim 3, characterized in that: The process of extracting the matching auxiliary step includes: Perform screening transformation on the matching auxiliary steps to obtain the target step signal; Perform element design on the attribute interaction matrix to obtain conversion extraction coefficients; The target step signal is compared and extracted according to the conversion extraction coefficient to obtain the initial activity coefficient.

5. The AR technology-based children's wearable assistance system according to claim 4, characterized in that: The process of deforming and updating the attribute interaction matrix through the initial activity coefficient includes: Performing deformation transformation on the obtained initial activity coefficient to obtain shape parameters; According to the obtained shape parameters, the initial activity coefficient is subjected to margin statistics to obtain the deformation interval; The deformation number is obtained according to the obtained shape parameters and deformation intervals, and the attribute interaction matrix is ​​initialized according to the deformation number to obtain an initial attribute matrix.

6. The AR technology-based children's wearable assistance system according to claim 5, characterized in that: The process of the auxiliary design module replacing elements of the initial attribute matrix includes: Obtain the deformation number, segment and collect the initial activity coefficient according to the deformation number, and obtain the initial deformation coefficient segment; The initial attribute matrix is ​​initially replaced according to the obtained initial deformation coefficient segment to obtain the deformation attribute matrix.

7. The AR technology-based children's wearable assistance system according to claim 6, characterized in that: The process of capturing motion features of a standard wearable capture image through a deformation attribute matrix includes: Upload the deformation attribute matrix to the starting point of the standard wearable capture image to obtain the attribute screening area; The attribute screening area is extracted within the area through the deformation attribute matrix to obtain the attribute extraction block; A smoothing interval is set for the deformation attribute matrix, and the deformation attribute matrix is ​​translated and slid based on the smoothing interval to reach the next attribute screening area, and the area is extracted with the attribute screening area until the cutoff point of the standard wearable capture image is reached; Based on the standard wear capture graph, the attribute extraction blocks are combined to obtain the wear feature graph. The AR technology-based child wearing assistance system according to claim 7 is characterized in that the process of performing intelligent prediction assistance on the target user through the wearing feature sequence includes: Obtaining a wearing feature graph, and sorting the wearing feature graph based on the target auxiliary step to obtain a wearing feature sequence; Upload the wearing feature sequence to the wearing auxiliary device, and use the wearing auxiliary device for auxiliary display to obtain the target wearing path; Based on the wearing auxiliary device, the target user is matched and positioned according to the target wearing path to obtain the user's wearing stage; According to the target wearing path, real-time prediction assistance is performed on the obtained user wearing stage until the target user completes the target wearing path.

8. The child wearing assistance method of the child wearing assistance system based on AR technology according to any one of claims 1 to 7, characterized in that: The following steps are involved: Step 1: Collect wearable capture data; Step 2: Construct an attribute interaction matrix, screen and match the wearable capture data, obtain matching auxiliary steps, extract and transform the matching auxiliary steps, obtain the initial activity coefficient, and deform and update the attribute interaction matrix through the initial activity coefficient to obtain the initial attribute matrix; Step 3: Replace the elements of the initial attribute matrix to obtain a deformation attribute matrix, and use the deformation attribute matrix to capture the motion features of the standard wearable capture image to obtain a wearable feature image; Step 4: Generate a wearing feature sequence based on the wearing feature graph, and use the wearing feature sequence to assist in intelligent prediction of the target user.

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