Generation and management system of 3D beauty model effect library based on multi-dimensional feature data

Abstract

The present invention relates to the technical field of generation and management of a 3D beauty model effect library, and specifically discloses a generation and management system of a 3D beauty model effect library based on multidimensional feature data, the system comprising: a 3D beauty model design module, a beauty satisfaction analysis module, a beauty improvement analysis module, a beauty stability analysis module, a beauty effect evaluation module and a beauty model effect library update module; the present invention comprehensively analyzes the beauty effect of each beauty user from three aspects of beauty satisfaction, beauty improvement and beauty stability, and manages the 3D beauty model effect library in combination with the beauty effect and access popularity of each 3D beauty model stored corresponding to each beauty demand, thereby realizing multi-angle analysis of the beauty effect and helping to meet the expectations of the beauty users. At the same time, the management of the 3D beauty model effect library can avoid repeated creation or storage of models with similar effects, thereby avoiding wasting time and resources.

Description

Technical Field

[0001] The present invention relates to the technical field of generation management of a 3D beauty model effect library, and in particular to a generation management system of a 3D beauty model effect library based on multi-dimensional feature data. Background Art

[0002] With the rapid development of the beauty industry, the demand for precise and personalized services is growing. However, traditional methods have many shortcomings in diagnosing facial problems and designing beauty plans, making it difficult to make accurate diagnoses. In addition, existing 3D modeling systems focus on single-dimensional data processing, making it difficult to fully reflect facial features and their changes.

[0003] For example, the patent with publication number CN107016244A discloses a cosmetic surgery effect evaluation system and implementation method, including: an image and video processing module, an industry expert evaluation module and an intelligent robot evaluation module, wherein the intelligent robot evaluation module learns and corrects the evaluation behavior of the cosmetic surgery effect of the industry experts, and then evaluates the cosmetic surgery effect of the target human body, and gives the scoring result and the basis for the scoring. The present invention provides a basis for measuring the service quality of doctors and medical cosmetic medical institutions, and for medical commercial insurance institutions to formulate premium rates.

[0004] The above existing technologies still have the following problems: 1) The current beauty effect analysis of 3D beauty models focuses on single-dimensional data processing, and does not combine multi-dimensional feature data to conduct a comprehensive analysis of the beauty effect, resulting in one-sided analysis results, unable to fully capture the key factors affecting the beauty effect, and difficult to formulate a completely personalized beauty plan, thus failing to meet customer expectations.

[0005] 2) The beauty effects of beauty users are not tracked over the long term, so the changes in the skin condition of beauty users cannot be intuitively displayed, and the sustainability and stability of the beauty effects cannot be accurately evaluated.

[0006] 3) The current management of the 3D beauty model effect library does not conduct a comprehensive analysis of the beauty effect evaluation index and access popularity of each 3D beauty model stored in response to each beauty need, which may lead to repeated creation or storage of models with similar effects, wasting time and resources. At the same time, when deciding to use or promote a certain model, the lack of data support based on evaluation index and popularity may lead to wrong decisions. Summary of the invention

[0007] In view of this, in order to solve the problems raised in the above background technology, a generation and management system of a 3D beauty model effect library based on multi-dimensional feature data is proposed.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a generation and management system for a 3D beauty model effect library based on multi-dimensional feature data, including: a 3D beauty model design module, which is used to collect the initial facial images of each beauty user in the target beauty salon, obtain the skin condition values ​​of each beauty user in the initial state, and collect the beauty needs of each beauty user, design the initial 3D beauty model effect diagram corresponding to each beauty user, and obtain the skin condition values ​​of each beauty user in the beauty design state.

[0009] The beauty satisfaction analysis module is used to collect the satisfaction scores of each beauty user after the beauty treatment is completed, and to extract the satisfaction scores of each beauty user on the beauty effect during each return visit, and to analyze the beauty satisfaction of each beauty user in the target beauty salon.

[0010] The beauty improvement degree analysis module is used to collect facial images of each beauty user after the beauty treatment is completed, obtain the skin condition values ​​of each beauty user after the beauty treatment is completed, and analyze the beauty improvement degree of each beauty user in the target beauty salon.

[0011] The beauty stability analysis module is used to collect the skin condition values ​​of each beauty user in each return visit and analyze the beauty stability of each beauty user in the target beauty salon.

[0012] The beauty effect evaluation module is used to calculate the beauty effect evaluation index of each beauty user in the target beauty salon.

[0013] The beauty model effect library update module is used to obtain the 3D beauty model effect pictures of each beauty user after the beauty treatment is completed, and to extract the stored beauty demand types and the beauty effect evaluation index and historical access information of each 3D beauty model stored corresponding to each beauty demand from the existing 3D beauty model effect library of the target beauty salon, and update the existing 3D beauty model effect library of the target beauty salon.

[0014] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention analyzes the beauty satisfaction, beauty improvement and beauty stability of each beauty user in the target beauty salon, thereby comprehensively analyzing the beauty effect evaluation index of each beauty user in the target beauty salon, thereby realizing a multi-faceted and multi-angle analysis of the beauty effect, avoiding the one-sidedness of the analysis results, and can comprehensively capture the key factors affecting the beauty effect, helping to formulate a completely personalized beauty plan to meet the expectations of customers.

[0015] (2) The present invention analyzes the beauty stability of each beauty user in the target beauty salon by combining the skin condition values ​​of each beauty user in each follow-up visit. By tracking the beauty effects of the beauty users over a long period of time, the changes in the skin conditions of the beauty users are intuitively displayed, and the sustainability and stability of the beauty effects are accurately evaluated.

[0016] (3) The present invention manages the 3D beauty model effect library by combining the beauty effect evaluation index and access popularity of each 3D beauty model stored in the 3D beauty model effect library corresponding to each beauty need, thereby avoiding repeated creation or storage of models with similar effects, avoiding waste of time and resources, and avoiding lack of data support based on evaluation index and popularity when deciding to use or promote a certain model, thereby avoiding decision-making errors caused by lack of data support based on evaluation index and popularity. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the system module structure connection of the present invention.

[0019] Figure 2 It is a schematic diagram of the skin condition value change curve of the beauty users in the return visit of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.

[0021] See also Figure 1 As shown, the present invention provides a generation and management system for a 3D beauty model effect library based on multi-dimensional feature data, including: a 3D beauty model design module, a beauty satisfaction analysis module, a beauty improvement analysis module, a beauty stability analysis module, a beauty effect evaluation module and a beauty model effect library update module.

[0022] The beauty satisfaction analysis module, the beauty improvement analysis module and the beauty stability analysis module are all connected to the beauty effect evaluation module, the beauty effect evaluation module and the beauty model effect library update module are both connected, and the 3D beauty model design module is connected to both the beauty improvement analysis module and the beauty stability analysis module.

[0023] The 3D beauty model design module is used to collect the initial facial images of each beauty user in the target beauty salon, obtain the skin condition values ​​of each beauty user in the initial state, collect the beauty needs of each beauty user, design the initial 3D beauty model renderings corresponding to each beauty user, and obtain the skin condition values ​​of each beauty user in the beauty design state.

[0024] It should be noted that the initial facial image of each beauty user in the target beauty salon is acquired by collecting it with a high-definition camera.

[0025] It should be noted that the skin condition values ​​of the beauty users in the initial state are obtained in the following manner: In a specific embodiment of the present invention, the skin condition values ​​include but are not limited to skin surface texture roughness, skin brightness, number of fine lines on the skin surface, number of acne on the skin surface, and skin surface color spot area. The texture analysis tool of the image processing software is used to measure the skin surface texture roughness, the color analysis tool is used to extract the skin brightness, the image enhancement and edge detection functions of the image processing software are used to highlight the number of fine lines on the skin surface and the number of acne on the skin surface, and the selection tool of the image processing software is used to measure the skin surface color spot area.

[0026] It should also be noted that the method for obtaining the skin condition values ​​of each beauty user in the initial state, in the beauty design state and in the beauty completion state is exactly the same. Here, the method for obtaining the skin condition values ​​of each beauty user in the initial state is taken as an example for explanation, and other details are not repeated.

[0027] In a specific embodiment of the present invention, the beauty needs include but are not limited to freckle removal, acne removal, skin whitening and rejuvenation, sensitive skin repair, wrinkle removal and anti-aging.

[0028] In a specific embodiment of the present invention, the method of designing the initial 3D beauty model rendering corresponding to each beauty user is: importing the collected initial facial images of each beauty user into the 3D modeling software of the target beauty salon to obtain the initial facial 3D model of each beauty user, and then fine-tuning the initial facial 3D model according to the beauty needs of each beauty user, and finally obtaining the initial 3D beauty model rendering corresponding to each beauty user.

[0029] The beauty satisfaction analysis module is used to collect the satisfaction scores of each beauty user after the beauty treatment is completed, and to extract the satisfaction scores of each beauty user on the beauty effect in each return visit, so as to analyze the beauty satisfaction of each beauty user in the target beauty salon.

[0030] It should be noted that the satisfaction scores of the beauty users after the beauty treatment and the satisfaction scores of the beauty effects in each return visit are extracted from the satisfaction score table.

[0031] In a specific embodiment of the present invention, the specific process of analyzing the beauty satisfaction of each beauty user in the target beauty salon is as follows: A1. The satisfaction score of each beauty user after the beauty treatment is completed is recorded as ε i , where i represents the number of the beauty user, i=1,2,...,n.

[0032] A2. Extract the minimum value from the satisfaction scores of each beauty user on the beauty effect in each return visit and record it as

[0033] A3. Calculate the beauty satisfaction β of each beauty user in the target beauty salon i .

[0034] It should be noted that the formula for calculating the beauty satisfaction of each beauty user in the target beauty salon is: Among them, ε′ and Δε represent the satisfaction score and satisfaction score deviation of the set reference, respectively.

[0035] The beauty improvement degree analysis module is used to collect facial images of each beauty user after beauty treatment, obtain the skin condition values ​​of each beauty user after beauty treatment, and analyze the beauty improvement degree of each beauty user in the target beauty salon.

[0036] It should be noted that the facial images of the beauty users after the beauty treatment are acquired through a high-definition camera.

[0037] In a specific embodiment of the present invention, the specific process of analyzing the beauty improvement degree of each beauty user in the target beauty salon is as follows: B1, recording the skin condition values ​​of each beauty user in the initial state, in the beauty design state and in the beauty completion state as and Here, g represents the number of the skin condition value, g=1, 2, ..., r.

[0038] B2. Calculate the facial change degree χ of each beauty user i , Wherein, e represents a natural constant, r represents the number of skin condition values, and Δτ′ represents a set reference skin condition change value.

[0039] B3. Calculate the beauty technology level of each beauty user δ i .

[0040] In a specific embodiment of the present invention, the formula for calculating the beauty technology achievement level of each beauty user is: Here, Δτ″ represents the deviation of the skin condition value of the set reference.

[0041] B4. Calculate the beauty improvement degree ω of each beauty user in the target beauty saloni , Among them, a1 and a2 represent the weights of the cosmetic improvement assessment corresponding to the set facial change degree and cosmetic technology standard degree, respectively, a1+a2=1.

[0042] In a specific embodiment of the present invention, the setting value of a1 is 0.5, and the setting value of a2 is 0.5. The facial change degree directly reflects the degree of improvement of the beauty project on the customer's facial skin or morphology, which is the effect that the customer can most intuitively feel. Therefore, when evaluating the degree of beauty improvement, the facial change degree is often regarded as an important quantitative indicator. The degree of compliance with beauty technology is also related to the long-term and stability of the beauty effect. If the technology does not meet the standards, even if it seems to be effective in the short term, the long-term effect may not be good or there may be safety hazards. Therefore, in actual evaluations, the facial change degree and the degree of compliance with beauty technology often need to be considered comprehensively.

[0043] The beauty stability analysis module is used to collect the skin condition values ​​of each beauty user in each return visit and analyze the beauty stability of each beauty user in the target beauty salon.

[0044] See also Figure 2 As shown, in a specific embodiment of the present invention, the specific process of analyzing the beauty stability of each beauty user in the target beauty salon is as follows: C1, with the number of return visits as the horizontal coordinate and the skin condition value as the vertical coordinate, a change curve of each skin condition value of each beauty user in the return visit is constructed, and the slope value is located from the curve as the change rate of each skin condition of each beauty user in the return visit, which is marked as K ig .

[0045] C2. Calculate the beauty stability of each beauty user in the target beauty salon Here, K′ represents the skin condition change rate of the set reference.

[0046] The embodiment of the present invention analyzes the beauty stability of each beauty user in the target beauty salon by combining the skin condition values ​​of each beauty user in each return visit, and intuitively displays the changes in the skin condition of the beauty users by tracking the beauty effects of the beauty users in the long term, so as to accurately evaluate the sustainability and stability of the beauty effects.

[0047] The beauty effect evaluation module is used to calculate the beauty effect evaluation index of each beauty user in the target beauty salon.

[0048] In a specific embodiment of the present invention, the formula for calculating the beauty effect evaluation index of each beauty user in the target beauty salon is: Among them, ψ irepresents the beauty effect evaluation index of the i-th beauty user in the target beauty salon, a3, a4 and a5 represent the weights of the beauty effect evaluation corresponding to the set beauty satisfaction, beauty improvement and beauty stability, respectively, a3+a4+a5=1.

[0049] In a specific embodiment of the present invention, the setting value of a3 is 0.32, the setting value of a4 is 0.34, and the setting value of a5 is 0.34. Beauty satisfaction directly reflects the customer's overall feeling about the beauty service, and is an indispensable part of evaluating the beauty effect. The beauty improvement degree measures the improvement degree of the beauty project on the customer's skin or morphology through quantitative indicators, and is an important quantitative standard for evaluating the beauty effect. The beauty stability reflects the durability and stability of the beauty effect, and is an important indicator for evaluating the long-term effect of the beauty project. If the beauty effect cannot be maintained for a long time, then even if the effect is significant in the short term, it will be difficult to gain the customer's long-term trust and recognition.

[0050] The embodiment of the present invention analyzes the beauty satisfaction, beauty improvement and beauty stability of each beauty user in the target beauty salon, thereby comprehensively analyzing the beauty effect evaluation index of each beauty user in the target beauty salon, realizing a multi-faceted and multi-angle analysis of the beauty effect, avoiding the one-sidedness of the analysis results, and can comprehensively capture the key factors affecting the beauty effect, helping to formulate a completely personalized beauty plan to meet the expectations of customers.

[0051] The beauty model effect library update module is used to obtain the 3D beauty model effect pictures of each beauty user after the beauty treatment is completed, and extract the stored beauty demand types and the beauty effect evaluation index and historical access information of each 3D beauty model stored corresponding to each beauty demand from the existing 3D beauty model effect library of the target beauty salon, and update the existing 3D beauty model effect library of the target beauty salon.

[0052] It should be noted that the 3D beauty model renderings of each beauty user after the beauty treatment are obtained by importing the facial images of each beauty user after the beauty treatment into the 3D modeling software of the target beauty salon to obtain the 3D beauty model renderings of each beauty user after the beauty treatment is completed.

[0053] In a specific embodiment of the present invention, the historical visit information includes the number of visits, the visit time point and the visit duration corresponding to each visit.

[0054] In a specific embodiment of the present invention, the specific process of updating the existing 3D beauty model effect library of the target beauty salon is as follows: D1. Compare the beauty needs of each beauty user with the types of beauty needs stored in the existing 3D beauty model effect library of the target beauty salon. If the beauty needs of a beauty user are not among the types of beauty needs stored in the 3D beauty model effect library, then the 3D beauty model effect image of the beauty user after the beauty treatment is completed is stored in the 3D beauty model effect library. Otherwise, the remaining beauty users are recorded as target beauty users.

[0055] D2. Compare the beauty needs of each target beauty user with the beauty needs stored in the 3D beauty model effect library, obtain the 3D beauty models with the same beauty needs of each target beauty user, and compare the beauty effect evaluation index of each target beauty user with the beauty effect evaluation index of each 3D beauty model with the same beauty need.

[0056] D3. If the beauty effect evaluation index of a target beauty user is greater than the beauty effect evaluation index of each 3D beauty model with the same beauty need, the 3D beauty model effect image of the target beauty user after the beauty treatment is completed is stored in the 3D beauty model effect library.

[0057] D4. If the beauty effect evaluation index of a target beauty user is smaller than the beauty effect evaluation index of each 3D beauty model with the same beauty need, the 3D beauty model effect image of the target beauty user after the beauty treatment is completed will not be stored in the 3D beauty model effect library.

[0058] D5. If the beauty effect evaluation index of a target beauty user is greater than the beauty effect evaluation index of certain 3D beauty models with the same beauty needs, the target beauty user is recorded as a reference beauty user, and the 3D beauty model with a beauty effect evaluation index less than that of the target beauty user is recorded as a reference beauty model.

[0059] D6. Conduct a new round of comparative analysis between each reference beauty user and each reference beauty model with the same beauty needs.

[0060] In a specific embodiment of the present invention, the specific process of performing a new round of comparative analysis on each reference beauty user and each reference beauty model having the same beauty need is as follows: E1, extracting the number of visits, the visit time point and the visit stay duration corresponding to each visit from the historical visit information of each 3D beauty model stored corresponding to each beauty need, and calculating the visit popularity ζ of each 3D beauty model stored corresponding to each beauty need. pq , where p represents the number of the beauty requirement, p=1,2,...,f, and q represents the number of the 3D beauty model, q=1,2,...,w.

[0061] It should be noted that the specific process of calculating the visit popularity of each 3D beauty model stored corresponding to each beauty demand is as follows: the number of visits of each 3D beauty model stored corresponding to each beauty demand is recorded as σ pq .

[0062] The access time points corresponding to each visit of each 3D beauty model stored corresponding to each beauty demand are compared with each other to obtain the access intervals of each 3D beauty model stored corresponding to each beauty demand, and the minimum value is extracted from them, which is recorded as

[0063] The minimum value is extracted from the visit duration corresponding to each visit of each 3D beauty model stored corresponding to each beauty demand, and recorded as

[0064] Calculate the access popularity of each 3D beauty model stored corresponding to each beauty demand pq , Among them, σ′, T 间 and T 停 They respectively represent the number of visits, visit interval duration and visit stay duration of the set reference.

[0065] E2. Extract the access popularity of each reference beauty user and each reference beauty model having the same beauty need as the reference beauty user from the access popularity of each 3D beauty model stored corresponding to each beauty need, and compare it with the access popularity of the set reference. If the access popularity of a reference beauty model is greater than or equal to the access popularity of the set reference, then the reference beauty model will continue to be stored in the 3D beauty model effect library, and the 3D beauty model effect image of the reference beauty user after the beauty treatment is completed will also be stored in the 3D beauty model effect library. Otherwise, the reference beauty model will be deleted from the 3D beauty model effect library, and the 3D beauty model effect image of the reference beauty user after the beauty treatment is completed will be stored in the 3D beauty model effect library.

[0066] D7. In summary, the updating process of the existing 3D beauty model effect library of the target beauty salon is obtained.

[0067] The embodiment of the present invention manages the 3D beauty model effect library by combining the beauty effect evaluation index and access popularity of each 3D beauty model stored corresponding to each beauty demand stored in the 3D beauty model effect library, thereby avoiding repeated creation or storage of models with similar effects, avoiding waste of time and resources, and avoiding lack of data support based on evaluation index and popularity when deciding to use or promote a certain model, thereby avoiding decision-making errors caused by lack of data support based on evaluation index and popularity.

[0068] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A generation and management system for a 3D beauty model effect library based on multi-dimensional feature data, characterized in that: include: The 3D beauty model design module is used to collect the initial facial images of each beauty user in the target beauty salon, obtain the skin condition values ​​of each beauty user in the initial state, collect the beauty needs of each beauty user, design the initial 3D beauty model effect diagram corresponding to each beauty user, and obtain the skin condition values ​​of each beauty user in the beauty design state; The beauty satisfaction analysis module is used to collect the satisfaction scores of each beauty user after the beauty treatment is completed, extract the satisfaction scores of each beauty user on the beauty effect during each return visit, and analyze the beauty satisfaction of each beauty user in the target beauty salon; The beauty improvement degree analysis module is used to collect facial images of each beauty user after the beauty treatment is completed, obtain the skin condition values ​​of each beauty user after the beauty treatment is completed, and analyze the beauty improvement degree of each beauty user in the target beauty salon; The beauty stability analysis module is used to collect the skin condition values ​​of each beauty user in each return visit and analyze the beauty stability of each beauty user in the target beauty salon; A beauty effect evaluation module is used to calculate the beauty effect evaluation index of each beauty user in the target beauty salon; The beauty model effect library update module is used to obtain the 3D beauty model effect pictures of each beauty user after the beauty treatment is completed, and extract the beauty demand types and the beauty effect evaluation index and historical access information of each 3D beauty model stored corresponding to each beauty demand from the existing 3D beauty model effect library of the target beauty salon, and update the existing 3D beauty model effect library of the target beauty salon; The specific process of analyzing the beauty satisfaction of each beauty user in the target beauty salon is as follows: A1. The satisfaction score of each beauty user after the beauty treatment is recorded as ,in, Indicates the beauty user's ID, ; A2. Extract the minimum value from the satisfaction scores of each beauty user on the beauty effect in each return visit and record it as ; A3. Calculate the beauty satisfaction of each beauty user in the target beauty salon ; The specific process of analyzing the beauty improvement degree of each beauty user in the target beauty salon is as follows: B1. Record the skin condition values ​​of each beauty user in the initial state, in the beauty design state, and in the beauty completion state as , and ,in, A number representing the skin status value. ; B2. Calculate the facial variation of each beauty user , ,in, represents a natural constant, Indicates the number of skin status values, Indicates the skin state change value of the set reference; B3. Calculate the beauty technology level of each beauty user ; B4. Calculate the beauty improvement degree of each beauty user in the target beauty salon , ,in, and They represent the weights of the cosmetic improvement assessment corresponding to the set facial change degree and cosmetic technology compliance degree, respectively. ; The formula for calculating the beauty technology achievement level of each beauty user is: ,in, Indicates the deviation of the skin condition value of the set reference; The specific process of analyzing the beauty stability of each beauty user in the target beauty salon is as follows: C1. Using the number of return visits as the horizontal coordinate and the skin condition value as the vertical coordinate, a curve of the change of each skin condition value of each beauty user in the return visit is constructed, and the slope value is located from the curve as the change rate of each skin condition of each beauty user in the return visit, which is marked as ; C2. Calculate the beauty stability of each beauty user in the target beauty salon , ,in, Indicates the skin condition change rate of the set reference; The formula for calculating the beauty effect evaluation index of each beauty user in the target beauty salon is: ,in, Indicates the target beauty salon The beauty effect evaluation index of beauty users, , and They represent the weights of the cosmetic effect evaluation corresponding to the cosmetic satisfaction, cosmetic improvement and cosmetic stability, respectively. .

2. The generation and management system of the 3D beauty model effect library based on multi-dimensional feature data according to claim 1, characterized in that: The method for designing the initial 3D beauty model rendering corresponding to each beauty user is as follows: the collected initial facial images of each beauty user are imported into the 3D modeling software of the target beauty salon to obtain the initial facial 3D model of each beauty user, and then the initial facial 3D model is finely adjusted according to the beauty needs of each beauty user, and finally the initial 3D beauty model rendering corresponding to each beauty user is obtained.

3. The generation and management system of the 3D beauty model effect library based on multi-dimensional feature data according to claim 1, characterized in that: The historical visit information includes the number of visits, the visit time point and the visit duration corresponding to each visit.

4. The generation and management system of the 3D beauty model effect library based on multi-dimensional feature data according to claim 3, characterized in that: The specific process of updating the existing 3D beauty model effect library of the target beauty salon is as follows: D1. Compare the beauty needs of each beauty user with the beauty need types stored in the existing 3D beauty model effect library of the target beauty salon. If the beauty need of a beauty user is not in the beauty need types stored in the 3D beauty model effect library, the 3D beauty model effect image of the beauty user after the beauty treatment is completed is stored in the 3D beauty model effect library. Otherwise, the remaining beauty users are recorded as target beauty users. D2. Compare the beauty needs of each target beauty user with the beauty needs stored in the 3D beauty model effect library, obtain the 3D beauty models with the same beauty needs of each target beauty user, and compare the beauty effect evaluation index of each target beauty user with the beauty effect evaluation index of each 3D beauty model with the same beauty need; D3. If the beauty effect evaluation index of a target beauty user is greater than the beauty effect evaluation index of each 3D beauty model with the same beauty needs, the 3D beauty model effect image of the target beauty user after the beauty treatment is completed is stored in the 3D beauty model effect library; D4. If the beauty effect evaluation index of a target beauty user is lower than the beauty effect evaluation index of each 3D beauty model with the same beauty need, the 3D beauty model effect image of the target beauty user after the beauty treatment is completed will not be stored in the 3D beauty model effect library; D5. If the beauty effect evaluation index of a target beauty user is greater than the beauty effect evaluation index of some 3D beauty models with the same beauty needs, the target beauty user is recorded as a reference beauty user, and the 3D beauty model with a beauty effect evaluation index less than that of the target beauty user is recorded as a reference beauty model; D6. Conduct a new round of comparative analysis between each reference beauty user and each reference beauty model with the same beauty needs; D7. In summary, the updating process of the existing 3D beauty model effect library of the target beauty salon is obtained.

5. The generation and management system of the 3D beauty model effect library based on multi-dimensional feature data according to claim 4, characterized in that: The specific process of performing a new round of comparative analysis on each reference beauty user and each reference beauty model having the same beauty needs is as follows: E1. Extract the number of visits, the visit time point and the visit duration corresponding to each visit from the historical visit information of each 3D beauty model stored corresponding to each beauty demand, and calculate the visit popularity of each 3D beauty model stored corresponding to each beauty demand ,in, A number indicating the beauty need. , Indicates the number of the 3D beauty model. ; E2. Extract the access popularity of each reference beauty user and each reference beauty model having the same beauty need as the reference beauty user from the access popularity of each 3D beauty model stored corresponding to each beauty need, and compare it with the access popularity of the set reference. If the access popularity of a reference beauty model is greater than or equal to the access popularity of the set reference, then the reference beauty model will continue to be stored in the 3D beauty model effect library, and the 3D beauty model effect image of the reference beauty user after the beauty treatment is completed will also be stored in the 3D beauty model effect library. Otherwise, the reference beauty model will be deleted from the 3D beauty model effect library, and the 3D beauty model effect image of the reference beauty user after the beauty treatment is completed will be stored in the 3D beauty model effect library.

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