Face repair system and face repair method

Abstract

The invention provides a face repair system and method, and the system comprises an image obtaining module which is configured to obtain a face image of a user; the image analysis module is configured to analyze the facial image to obtain facial feature data and skin quantitative index data of the user; the repair mask model matching module is configured to determine the facial form of the user according to the facial feature data of the user and determine the repair mask model corresponding to the user according to the facial form of the user; and the essence type matching module is configured to determine the skin state type of the user according to the skin quantitative index data of the user, and determine the essence type corresponding to the user according to the skin state type of the user. Accurate matching of the repair mask model and the user face shape can be achieved, dynamic matching of the essence type and the user skin state can be achieved, and the face repair effect is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of facial repair technology, and in particular to a facial repair system and a facial repair method. Background Technology

[0002] While the current facial repair market offers a wide variety of products, user experience and effectiveness still face systemic bottlenecks. Industry research and user feedback analysis have identified the core issues in the following three areas:

[0003] (1) Product suitability is seriously out of sync with individual differences.

[0004] Most mainstream sheet-type repair masks on the market use a "one-size-fits-all" design, which makes it difficult to match the significant facial diversity of Asian people (such as anatomical differences in cheekbone height, jaw angle, and nasolabial fold depth). Users often experience issues like the mask lifting at the cheekbone and slipping off the jawline, leading to localized loss of the essence and uneven penetration of active ingredients. The root cause lies in the fact that traditional repair mask production relies on standardized molds to control costs, while personalized customization requires precise facial measurements and flexible manufacturing. The existing industry chain lacks a rapid-response closed loop of "identification-design-production." Furthermore, most products only focus on surface skin problems (such as dryness and dullness), neglecting the decisive influence of the three-dimensional facial structure on product fit.

[0005] (2) The repair plan lacks dynamic precision.

[0006] When choosing serums, users often rely on subjective feelings (such as "feeling dry") or marketing claims, rather than scientific judgments based on the real-time condition of their skin. Even when some products incorporate skin testing equipment, the output results (such as hydration level and wrinkle index) are only used as a single reference and fail to link with subsequent repair products. The underlying problem lies in the fact that skin conditions are dynamic and time-dependent (such as hormonal fluctuations during menstruation and the influence of environmental changes), while current technologies separate "detection" from "intervention." The detection stage is mostly completed by third-party equipment, while the repair stage relies on fixed-formula products. There is a lack of data flow mechanisms and intelligent decision-making logic between the two, resulting in rigid solutions and a high risk of mismatch.

[0007] (3) Lack of effectiveness evaluation leads to a crisis of user trust.

[0008] Users often struggle to quantify the repair effects and discontinue use due to perceived ineffectiveness, resulting in a persistently low repurchase rate in the industry. Existing products lack continuous tracking mechanisms, providing no data feedback after a single use, making it impossible for users to perceive subtle improvements (such as a 0.05mm change in fine line depth). The root cause lies in the fact that facial repair involves multiple variables (products, lifestyle, environment), requiring long-term, standardized data collection and analysis capabilities. However, current technological solutions often focus on single-point tools (such as photo-based skin analysis) and fail to construct a closed-loop system of "identification-intervention-retesting-optimization." Furthermore, cross-domain integration is challenging (requiring the fusion of computer vision, materials science, and skin physiology), leading to widespread data silos.

[0009] In summary, the core flaws of existing facial repair systems lie in the fundamental contradiction between "product standardization" and "personalized needs," as well as the technological gap between "isolated detection" and "dynamic intervention." These problems cannot be solved by optimizing a single aspect; a system-wide reconstruction is needed: organically integrating facial 3D structure recognition, temporal analysis of skin condition types, and a closed-loop user behavior data system. However, due to the high barriers to cross-disciplinary technology integration and the difficulty of supply chain collaboration, the industry has long been unable to overcome these bottlenecks, and users have an urgent need for highly efficient repair solutions that are "truly personalized and have verifiable effects."

[0010] It should be noted that the information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0011] The purpose of this invention is to provide a facial repair system and a facial repair method that can not only achieve precise matching between the repair mask model and the user's face shape, significantly improving the fit between the repair mask and the user's face, and avoiding displacement phenomena such as lifting at the cheekbone or hanging off the jawline when the user wears the repair mask, but also achieve dynamic matching between the essence type and the user's skin condition, effectively reducing the skin care risks caused by the user's misdiagnosis.

[0012] To achieve the above objectives, the present invention provides a facial repair system, comprising: an image acquisition module configured to acquire a user's facial image; an image analysis module configured to analyze the facial image to acquire the user's facial feature data and skin quantitative index data, wherein the facial feature data includes coordinates of multiple facial key points, and the skin quantitative index data includes barrier function data, pigmentation data, texture aging data, and water-oil balance data; a repair mask model matching module configured to determine the user's face shape based on the user's facial feature data, and determine the corresponding repair mask model based on the user's face shape; and an essence type matching module configured to determine the user's skin condition type based on the user's skin quantitative index data, and determine the corresponding essence type based on the user's skin condition type.

[0013] Further, determining the user's face shape based on the user's facial feature data includes: obtaining the user's key geometric parameter data based on the user's facial feature data, the key geometric parameter data including face length, face width, mandibular angle, cheekbone height ratio, philtrum length, nose length, and cheekbone prominence; and determining the user's face shape based on the user's key geometric parameter data.

[0014] Optionally, the user's face length is determined based on the absolute value of the difference between the Y-axis coordinates of the user's forehead key point and the Y-axis coordinates of the user's chin key point; the user's face width is determined based on the absolute value of the Y-axis coordinates of the user's right mandibular key point and the left mandibular key point; the user's mandibular angle is determined based on the angle between the line formed by the user's left mandibular key point and the chin key point and the line formed by the user's right mandibular key point and the chin key point; and the user's cheekbone is determined based on the absolute value of the difference between the Y-axis coordinates of the user's right cheekbone key point and the Y-axis coordinates of the nose tip key point. The height of the cheekbone is determined by the ratio of the user's cheekbone height to their face length; the length of the philtrum is determined by the absolute value of the difference between the Y-axis coordinates of the lower and upper edges of the philtrum; the length of the nose is determined by the absolute value of the difference between the Y-axis coordinates of the tip and bridge of the nose; the width of the cheekbone is determined by the absolute value of the difference between the X-axis coordinates of the right and left cheekbone points, and the cheekbone prominence is determined by the ratio of the cheekbone width to the face width.

[0015] Optionally, the key geometric parameter data also includes interpupillary distance, wherein the interpupillary distance of the user is determined based on the distance between the key points of the user's left and right pupils.

[0016] The step of determining the user's face shape based on the user's key geometric parameter data includes: if the user's cheekbone height ratio is greater than 0.14 and the mandibular angle is less than 112°, or the user's face length to interpupillary distance ratio is greater than 1.75, the philtrum length to interpupillary distance ratio is less than or equal to 0.25 and the mandibular angle is less than 112°, or the user's face length to face width ratio is less than 1.35 and the cheekbone prominence is greater than 0.85, then the user's face shape is determined to be a high cheekbone round face; if the user's mandibular angle... If the angle is greater than or equal to 112°, or the ratio of the user's face length to face width is less than 1.40 and the cheekbone prominence is less than or equal to 0.80, then the user's face shape is determined to be a wide-jawed square face; if the ratio of the user's face length to face width is greater than 1.65, or the ratio of the user's face length to interpupillary distance is greater than 1.85 and the ratio of philtrum length to interpupillary distance is greater than 0.25, or the ratio of the user's nose length to interpupillary distance is greater than 0.45 and the ratio of face length to face width is greater than 1.65, then the user's face shape is determined to be a long face.

[0017] Optionally, determining the appropriate repair mask model based on the user's face shape includes: if the user has a round face with high cheekbones, then a repair mask that extends the cheekbone area is determined as the appropriate repair mask model for the user; if the user has a square face with a wide jawline, then a repair mask that extends the jawline is determined as the appropriate repair mask model for the user; if the user has a long face, then a repair mask that extends the philtrum area and widens the forehead area is determined as the appropriate repair mask model for the user.

[0018] Optionally, the barrier function data includes estimated transepidermal water loss, redness index, and skin elasticity value; the pigmentation data includes the percentage of pigmentation area, skin tone evenness index, and dark circle brightness value; the texture aging data includes the depth of crow's feet, the depth of nasolabial folds, the depth of eye wrinkles, the volume of eye bags, and the blurring of the jawline; and the water-oil balance data includes the stratum corneum moisture content and facial puffiness index.

[0019] Optionally, determining the user's skin condition type based on the user's skin quantification index data includes: if the user's estimated transepidermal water loss is greater than 25 g·m³... -2If the user's skin condition is characterized by: a redness index greater than 2.5 and a stratum corneum moisture content less than 45%; a damaged skin barrier; crow's feet wrinkles greater than 0.20 mm and skin elasticity less than 45; pigmentation spots covering more than 5.0% of the skin and a skin tone evenness index less than 0.35; jawline blurring greater than 15% and facial puffiness greater than 0.4; and under-eye bags greater than 0.8 cm in volume. 3 If the brightness value of dark circles is less than 35 or the depth of eye wrinkles is greater than 0.15mm, then the user's skin condition is determined to be periorbital aging.

[0020] Optionally, determining the appropriate serum type for the user based on their skin condition includes: if the user's skin condition is a damaged skin barrier, then a repairing and moisturizing serum is selected as the appropriate serum type; if the user's skin condition is collagen loss, then an anti-wrinkle and plumping serum is selected as the appropriate serum type; if the user's skin condition is uneven skin tone, then a brightening and lifting serum is selected as the appropriate serum type; if the user's skin condition is sagging skin, then a lifting and firming serum is selected as the appropriate serum type; and if the user's skin condition is aging skin around the eyes, then an eye serum is selected as the appropriate serum type.

[0021] Optionally, the serum type matching module is further configured to dynamically adjust the serum type corresponding to the user based on the trend of changes in the user's skin quantitative index data within the most recent preset time period.

[0022] Optionally, the essence type matching module is further configured to: locate the weak areas on the user's face based on the user's skin quantitative index data, and generate a zoned repair plan based on the location results of the weak areas.

[0023] To achieve the above objectives, the present invention also provides a facial repair method, comprising: acquiring a user's facial image; analyzing the facial image to obtain the user's facial feature data and skin quantitative index data, wherein the facial feature data includes coordinates of multiple facial key points, and the skin quantitative index data includes barrier function data, pigmentation data, texture aging data, and water-oil balance data; determining the user's face shape based on the user's facial feature data, and determining the corresponding repair mask model based on the user's face shape; determining the user's skin condition type based on the user's skin quantitative index data, and determining the corresponding serum type based on the user's skin condition type.

[0024] Further, determining the user's face shape based on the user's facial feature data includes: obtaining the user's key geometric parameter data based on the user's facial feature data, the key geometric parameter data including face length, face width, mandibular angle, cheekbone height ratio, philtrum length, nose length, and cheekbone prominence; and determining the user's face shape based on the user's key geometric parameter data.

[0025] Compared with existing technologies, the facial repair system and method provided by this invention have the following beneficial effects: This invention, by acquiring facial feature data including the coordinates of multiple key facial points, can accurately determine the user's face shape. By determining the appropriate repair mask model based on the user's face shape, it achieves precise matching between the repair mask model and the user's face shape, significantly improving the fit of the repair mask to the user's face and preventing displacement phenomena such as edge lifting at the cheekbones or jawline suspension when the user wears the repair mask. This effectively prevents problems such as localized loss of essence and uneven penetration of effective ingredients. Furthermore, by acquiring quantitative skin index data such as the user's barrier function, pigmentation, texture aging, and water-oil balance, this invention can accurately determine the user's skin condition type. By determining the appropriate essence type based on the user's skin condition type, it achieves dynamic matching between essence type and user's skin condition, effectively reducing skincare risks caused by user self-diagnosis errors and effectively improving facial repair effects. Furthermore, by obtaining key geometric parameters such as face length, face width, mandibular angle, cheekbone height ratio, philtrum length, nose length, and cheekbone prominence based on the user's facial feature data, the present invention can transform the vague concept of face shape into a set of quantifiable geometric parameters, thereby providing a scientific and objective basis for determining face shape. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the block structure of a facial repair system provided in one embodiment of the present invention.

[0027] Figure 2This is a schematic diagram of the unfolded structure of the repair film provided in one embodiment of the present invention.

[0028] Figure 3 A flowchart illustrating the dynamic adjustment of serum type in a facial repair system according to an embodiment of the present invention.

[0029] Figure 4 A flowchart of a facial repair method provided according to an embodiment of the present invention.

[0030] The reference numerals in the attached drawings are explained as follows: Image acquisition module - 110; Image analysis module - 120; Repairing mask model matching module - 130; Essence type matching module - 140; Slit - 210; V-shaped notch - 220; Ear loop - 230. Detailed Implementation

[0031] The facial repair system and method proposed in this invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Please refer to the accompanying drawings for a clearer understanding of the objectives, features, and advantages of this invention. It should be noted that the structures, proportions, sizes, etc., illustrated in the accompanying drawings are merely for illustrative purposes and to enable those skilled in the art to understand and read the invention. They are not intended to limit the implementation conditions of the invention. Any modifications to the structure, changes in proportions, or adjustments to the size, provided they produce the same or similar effects and achieve the same objectives as this invention, should still fall within the scope of the technical content disclosed in this invention.

[0032] The core idea of ​​this invention is to provide a facial repair system and a facial repair method that can not only achieve precise matching between the repair mask model and the user's face shape, significantly improving the fit between the repair mask and the user's face, and avoiding displacement phenomena such as lifting at the cheekbone or hanging off the jawline when the user wears the repair mask, but also achieve dynamic matching between the essence type and the user's skin condition, effectively reducing the skin care risks caused by the user's misdiagnosis.

[0033] It should be noted that the facial repair method provided by the present invention can be applied to the facial repair system provided by the present invention. The facial repair system can be configured on an electronic device, wherein the electronic device can be a personal computer, a mobile terminal, etc., and the mobile terminal can be a mobile phone, a tablet computer, or other hardware device with various operating systems.

[0034] To achieve the above-mentioned goals, this invention provides a facial repair system, please refer to... Figure 1 This is a schematic diagram of the block structure of a facial repair system provided in one embodiment of the present invention. Figure 1As shown, the facial repair system provided by the present invention includes: an image acquisition module 110, configured to acquire a user's facial image; an image analysis module 120, configured to analyze the facial image to acquire the user's facial feature data and skin quantitative index data, wherein the facial feature data includes coordinates of multiple facial key points, and the skin quantitative index data includes barrier function data, pigmentation data, texture aging data, and water-oil balance data; a repair mask model matching module 130, configured to determine the user's face shape based on the user's facial feature data, and determine the corresponding repair mask model based on the user's face shape; and an essence type matching module 140, configured to determine the user's skin condition type based on the user's skin quantitative index data, and determine the corresponding essence type based on the user's skin condition type.

[0035] Therefore, this invention, by acquiring facial feature data including the coordinates of multiple key facial points, can accurately determine the user's face shape. By determining the appropriate repair mask model based on the user's face shape, it achieves precise matching between the repair mask model and the user's face shape, significantly improving the fit of the repair mask to the user's face and preventing displacement phenomena such as lifting at the cheekbones or leaving the jawline unsupported. This effectively prevents problems such as localized loss of essence and uneven penetration of active ingredients. Furthermore, by acquiring quantitative skin index data such as the user's barrier function, pigmentation, texture aging, and water-oil balance, this invention can accurately determine the user's skin condition type. By determining the appropriate essence type based on the user's skin condition type, it achieves dynamic matching between essence type and user's skin condition, effectively reducing skincare risks caused by user self-diagnosis errors and effectively improving facial repair effects.

[0036] It should be noted that the facial image can be a three-dimensional facial image (resolution ≥1080P, automatic lighting correction) captured from multiple angles by a professional 3D skin detector. Furthermore, the user-uploaded facial image can be analyzed using third-party facial analysis scanning software and its database to obtain the user's facial feature data and skin quantitative index data. Further, the facial feature data includes the coordinates of 106 high-precision facial key points, specifically covering the following anatomical regions: 17 contour points such as the mandibular angle, chin tip, and highest point of the cheekbone; and 89 facial feature points such as the inner and outer canthi of the eye, the base of the nasal alar, and the corners of the mouth.

[0037] Furthermore, users can perform facial repair according to the determined repair mask model and essence type, wear it for at least 6 hours during sleep, and take a facial image the next morning to compare with the data from the previous day, thereby updating the user's skin condition database.

[0038] Further, determining the user's face shape based on the user's facial feature data includes: obtaining the user's key geometric parameter data based on the user's facial feature data, the key geometric parameter data including face length, face width, mandibular angle, cheekbone height ratio, philtrum length, nose length, and cheekbone prominence; and determining the user's face shape based on the user's key geometric parameter data.

[0039] Therefore, by obtaining key geometric parameters such as face length, face width, jaw angle, cheekbone height ratio, philtrum length, nose length and cheekbone prominence based on the user's facial feature data, the vague concept of face shape can be transformed into a set of quantifiable geometric parameters, thereby providing a scientific and objective basis for determining face shape.

[0040] In some exemplary implementations, the user's face length is determined based on the absolute value of the difference between the Y-axis coordinate value of the user's forehead key point and the Y-axis coordinate value of the chin key point.

[0041] Therefore, this setting can effectively reduce the computational complexity of the surface length, and has the advantages of fast processing speed, low latency, and low resource consumption.

[0042] In some exemplary embodiments, the user's face width is determined based on the absolute values ​​of the Y-axis coordinates of the user's right mandibular key point and the Y-axis coordinates of the user's left mandibular key point.

[0043] Therefore, this setting can effectively reduce the computational complexity of the area width, and has the advantages of fast processing speed, low latency, and low resource consumption.

[0044] In some exemplary embodiments, the user's mandibular angle is determined based on the angle between the line formed by the user's left mandibular key point and chin key point and the line formed by the user's right mandibular key point and chin key point.

[0045] Therefore, this setting can effectively reduce the computational complexity of the mandibular angle, and has the advantages of fast processing speed, low latency, and low resource consumption.

[0046] In some exemplary embodiments, the user's cheekbone height is determined based on the absolute value of the difference between the Y-axis coordinate value of the user's right cheekbone key point and the Y-axis coordinate value of the nose tip key point, and the user's cheekbone height ratio is determined based on the ratio of the user's cheekbone height to face length.

[0047] Therefore, this setting can effectively reduce the computational complexity of the cheekbone height ratio, and has the advantages of fast processing speed, low latency, and low resource consumption.

[0048] In some exemplary embodiments, the length of the user's philtrum is determined based on the absolute value of the difference between the Y-axis coordinate value of the lower edge key point of the philtrum and the Y-axis coordinate value of the upper edge key point of the philtrum.

[0049] Therefore, this setting can effectively reduce the computational complexity of philtrum length, and has the advantages of fast processing speed, low latency, and low resource consumption.

[0050] In some exemplary embodiments, the user's nose length is determined based on the absolute value of the difference between the Y-axis coordinate value of the user's nasal tip key point and the Y-axis coordinate value of the nasal bridge key point.

[0051] Therefore, this setting can effectively reduce the computational complexity of nose length, and has the advantages of fast processing speed, low latency, and low resource consumption.

[0052] In some exemplary embodiments, the user's cheekbone width is determined based on the absolute value of the difference between the X-axis coordinate value of the user's right cheekbone key point and the X-axis coordinate value of the user's left cheekbone key point, and the user's cheekbone prominence is determined based on the ratio of the user's cheekbone width to face width.

[0053] Therefore, this setting can effectively reduce the computational complexity of cheekbone prominence, and has the advantages of fast processing speed, low latency, and low resource consumption.

[0054] In some exemplary embodiments, the key geometric parameter data also includes interpupillary distance, wherein the interpupillary distance of the user is determined based on the distance between the key points of the user's left and right pupils.

[0055] Further, determining the user's face shape based on the user's key geometric parameter data includes: if the user's cheekbone height ratio is greater than 0.14 and the mandibular angle is less than 112°, or the user's face length to interpupillary distance ratio is greater than 1.75, the philtrum length to interpupillary distance ratio is less than or equal to 0.25 and the mandibular angle is less than 112°, or the user's face length to face width ratio is less than 1.35 and the cheekbone prominence is greater than 0.85, then the user's face shape is determined to be a high cheekbone round face; if the user's mandibular angle is less than 112°, the user's face shape is determined to be a high cheekbone round face. If the angle is greater than or equal to 112°, or the ratio of the user's face length to face width is less than 1.40 and the cheekbone prominence is less than or equal to 0.80, then the user's face shape is determined to be a wide-jawed square face; if the ratio of the user's face length to face width is greater than 1.65, or the ratio of the user's face length to interpupillary distance is greater than 1.85 and the ratio of philtrum length to interpupillary distance is greater than 0.25, or the ratio of the user's nose length to interpupillary distance is greater than 0.45 and the ratio of face length to face width is greater than 1.65, then the user's face shape is determined to be a long face.

[0056] In practical applications, the distance and angle at which users take photos are unlikely to be exactly the same. Therefore, directly using the original pixel distance will introduce errors due to the different shooting distances. This invention normalizes face length, philtrum length, and nose length using interpupillary distance as the reference unit (calculating the ratio of face length to interpupillary distance, the ratio of philtrum length to interpupillary distance, and the ratio of nose length to interpupillary distance), which can effectively ensure the accuracy of user face recognition results.

[0057] In some exemplary embodiments, determining the appropriate repair mask model for the user based on their face shape includes: if the user has a round face with high cheekbones, then a repair mask that extends the cheekbone area is determined as the appropriate repair mask model for the user; if the user has a square face with a wide jawline, then a repair mask that extends the jawline is determined as the appropriate repair mask model for the user; if the user has a long face, then a repair mask that extends the philtrum area and widens the forehead area is determined as the appropriate repair mask model for the user.

[0058] Therefore, this setting can further achieve a precise match between the repair mask model and the user's face shape, significantly improving the fit between the repair mask and the user's face, avoiding displacement phenomena such as lifting at the cheekbone or hanging off the jawline when the user wears the repair mask, and effectively preventing problems such as local loss of essence and uneven penetration of effective ingredients.

[0059] Specifically, for round faces with high cheekbones, the appropriate repair mask model can be extended by 1.5cm in the cheekbone area to meet the support needs of high cheekbones. For square faces with wide jawlines, the appropriate repair mask model can be extended by 1.2cm along the jawline to cover the wide jaw. For long faces, the appropriate repair mask model can be extended by 0.5cm at the philtrum and widened by 2cm at the forehead to cover the wide forehead and long philtrum.

[0060] To further enhance the fit of the repair mask to the user's face, the mask can be composed of a 3D micro-support structure and a silicone film. The 3D micro-support structure and the silicone film are firmly bonded together to form a unified structure, ensuring no delamination between them. Please continue to refer to [link / reference needed]. Figure 2 This is a schematic diagram of the unfolded structure of the repair film provided in one embodiment of the present invention. Figure 2As shown, the repair film has regularly arranged slits 210 on its surface. This design not only gives the repair film excellent flexibility and extensibility but also significantly improves its fit to the three-dimensional curves of the face (facial contours). Furthermore, due to the high oxygen permeability and biocompatibility of the silicone film itself, combined with the slit 210 design, it effectively promotes the exchange of air between the skin and the outside environment, maintaining a "breathing" environment for the skin during prolonged wear. This avoids the stuffiness, redness, or breakouts caused by traditional occlusive dressings, greatly improving comfort and safety. Simultaneously, the overall elasticity, deformation resistance, and mechanical stability of the 3D micro-support allow the repair film to remain in contact with the skin without shifting even after prolonged wear, creating ideal conditions for the long-lasting release of active ingredients and the regulation of the skin's microenvironment.

[0061] Furthermore, such as Figure 2 As shown, the repair mask has V-shaped notches 220 on both sides of the eyes and mouth. By setting V-shaped notches 220 on the repair mask, the mask fabric can be guided to transition along the high points of the face (such as the cheekbones), which can lift the jawline during use. At the same time, it can also ensure that it will not shift or wrinkle during long-term wear.

[0062] Furthermore, such as Figure 2 As shown, the repair film also has ear loops 230 on both sides. By setting ear loops 230 on the repair film, the elasticity and stability of the repair film in the undulating areas of the face can be further enhanced, which helps to achieve dynamic adhesion from a flat surface to three dimensions.

[0063] It should be noted that, as those skilled in the art will understand, the following can be used as... Figure 2 The entire repair film shown is precisely cut into different functional units through overcutting to meet the needs of zoned repair.

[0064] In some exemplary embodiments, the barrier function data includes estimated transepidermal water loss, redness index, and skin elasticity value; the pigmentation data includes the percentage of pigmentation area, skin tone evenness index, and dark circle brightness value; the texture aging data includes crow's feet depth, nasolabial fold depth, eye wrinkle depth, eye bag volume, and jawline blurring; and the water-oil balance data includes stratum corneum moisture content and facial puffiness index.

[0065] Therefore, this setting can provide good data support for accurately identifying the user's skin condition type, thus laying a good foundation for achieving accurate matching between serum type and user's skin condition.

[0066] Specifically, third-party facial analysis scanning software and its database can be used to analyze user-uploaded facial images to obtain estimated transepidermal water loss, redness index, skin elasticity value, pigmentation area ratio, skin tone evenness index, dark circle brightness value, crow's feet depth, nasolabial fold depth, eye wrinkle depth, eye bag volume, jawline blurring, stratum corneum water content, and facial edema index. The estimated transepidermal water loss can be obtained through multispectral imaging and convolutional neural network (CNN) analysis. Specifically, multispectral imaging can capture the spectral reflectance characteristics of different bands on the skin surface, and training a CNN can generate a model capable of estimating transepidermal water loss based on the spectral data of the user's facial skin. The redness index can be obtained by analyzing the reflectance intensity of specific bands (e.g., hemoglobin absorption peaks) through multispectral imaging and calculating the area of ​​the reddened facial region. The pigmentation area ratio can be obtained by extracting pigmented areas using image segmentation algorithms and then calculating the proportion of the pigmented area to the total number of pixels on the face. Skin tone evenness index can be obtained by calculating the standard deviation of brightness values ​​in various regions (e.g., left cheek, right cheek, forehead). Skin elasticity value can be obtained by acquiring a 3D facial model using 3D structured light reconstruction technology and analyzing the subtle undulations and texture features of the skin surface in its natural state. Dark circle brightness value can be obtained by extracting the periorbital area and calculating the average brightness value of that area. Crow's feet depth and eye wrinkle depth can be obtained by acquiring the detailed 3D topography of the periorbital area using 3D structured light reconstruction technology, identifying the lines of crow's feet and eye wrinkles, and calculating their depth relative to the surrounding skin. Nasolabial fold depth can be obtained by creating a 3D model of the nasolabial fold area using 3D structured light reconstruction technology and measuring the maximum or average depth of the folds. Eye bag volume can be obtained by reconstructing a facial model using 3D structured light reconstruction technology, comparing the eye bag area with surrounding smooth reference surfaces (e.g., the cheekbone area), and calculating the volume of the protruding part of the eye bag. Jawline blurring can be obtained by analyzing the 3D geometric features of the face, detecting the contour line of the lower edge of the mandible, and calculating the sharpness of the contour line of the lower edge of the mandible. Facial puffiness index can be obtained by acquiring a facial model using 3D structured light reconstruction technology and comparing it with a baseline facial model of the user without puffiness. The stratum corneum water content can be obtained by measuring the change in the polarization state of light reflected from the skin (water molecules have absorption peaks for specific wavelengths of near-infrared light).

[0067] In some exemplary embodiments, determining the user's skin condition type based on the user's skin quantification index data includes: if the user's estimated transepidermal water loss is greater than 25 g·m³. -2If the user's skin condition is characterized by: a redness index greater than 2.5 and a stratum corneum moisture content less than 45%; a damaged skin barrier; crow's feet wrinkles greater than 0.20 mm and skin elasticity less than 45; pigmentation spots covering more than 5.0% of the skin and a skin tone evenness index less than 0.35; jawline blurring greater than 15% and facial puffiness greater than 0.4; and under-eye bags greater than 0.8 cm in volume. 3 If the brightness value of dark circles is less than 35 or the depth of eye wrinkles is greater than 0.15mm, then the user's skin condition is determined to be periorbital aging.

[0068] Therefore, this setting can provide a theoretical basis for accurately judging the user's skin condition.

[0069] In some exemplary embodiments, determining the appropriate serum type for the user based on their skin condition includes: if the user's skin condition is a damaged skin barrier, then a repairing and moisturizing serum is selected as the appropriate serum type; if the user's skin condition is collagen loss, then an anti-wrinkle and plumping serum is selected as the appropriate serum type; if the user's skin condition is uneven skin tone, then a brightening and lifting serum is selected as the appropriate serum type; if the user's skin condition is sagging skin, then a lifting and firming serum is selected as the appropriate serum type; and if the user's skin condition is aging skin around the eyes, then an eye serum is selected as the appropriate serum type.

[0070] Therefore, this setting can better achieve dynamic matching between serum type and user's skin condition, effectively reducing skincare risks caused by user self-diagnosis errors, thereby effectively improving facial repair effects.

[0071] Specifically, the core active ingredients of repairing and moisturizing serums include plant exosomes (such as Centella asiatica) and ceramide complexes, whose mechanism of action is to repair the stratum corneum barrier and promote cell regeneration. The core active ingredients of anti-wrinkle and plumping serums include peptide complexes (such as a complex of acetyl hexapeptide-8 and palmitoyl tripeptide-5), whose mechanism of action is to promote collagen synthesis and smooth dynamic wrinkles. The core active ingredients of brightening and lifting serums include natural whitening complexes (such as a complex of horse chestnut extract and niacinamide derivatives), whose mechanism of action is to inhibit melanin transport and even out skin tone. The core active ingredients of lifting and firming serums include microcurrent-activated peptide (TDP-1) and caffeine derivatives, whose mechanism of action is to shrink subcutaneous tissue and improve facial contour. The core active ingredients of eye serums include hypoallergenic caffeine and sodium hyaluronate, whose mechanism of action is to promote microcirculation around the eyes and reduce puffiness and dark circles.

[0072] In some exemplary embodiments, the essence type matching module 140 is further configured to locate the weak areas of the user's face based on the user's skin quantitative index data, and generate a zoned repair plan based on the location results of the weak areas.

[0073] Therefore, this setting allows for zoned facial repair of the user's face, further improving the facial repair effect.

[0074] Specifically, based on the user's skin quantitative index data, the coordinates of problematic skin areas (weak areas) can be mapped to a repair film partition template (seven predefined repair areas: forehead, left cheekbone, right cheekbone, nasolabial fold, chin, left eye area, and right eye area) to generate a problem heat map.

[0075] Furthermore, when the user's estimated transdermal water loss is greater than 25 g·m -2 When the redness index is greater than 2.5 and the stratum corneum moisture content is less than 45%, the generated zoned repair plan can be: apply a repairing and moisturizing essence evenly to the entire face, with a focus on applying it to high-redness areas such as the cheekbones and the sides of the nose. When the user's crow's feet depth is greater than 0.20mm and nasolabial fold depth is greater than 1.8 lines / cm... 2When the skin elasticity value is less than 45, the generated zoned repair plan can be: avoid healthy skin areas and apply anti-wrinkle and plumping serum only to the eye area and nasolabial folds. When the user's left cheekbone pigmentation area accounts for more than 6.0%, the right cheekbone pigmentation area accounts for less than 3.0%, and the skin tone evenness index is less than 0.35, the generated zoned repair plan can be: apply brightening and lifting serum only to the left cheekbone area, and use basic moisturizing serum to the right cheekbone area. When the user's jawline blurring is greater than 15% and facial puffiness index is greater than 0.4, the generated zoned repair plan can be: apply lifting and firming serum along the jawline to the preauricular lymph node area, avoiding the eye area. When the user's eye bags are larger than 0.8cm... 3 If the brightness value of dark circles is less than 35 or the depth of fine lines around the eyes (eye wrinkle depth) is greater than 0.15mm, then apply eye serum only around the eyes (within 2mm of the lash line), and apply it less than or equal to twice each time.

[0076] In some exemplary embodiments, the serum type matching module 140 is further configured to dynamically adjust the serum type corresponding to the user based on the trend of changes in the user's skin quantitative index data within the most recent preset time period.

[0077] Therefore, this setting allows for dynamic adjustments to the skincare routine based on the changing trends of the user's skin condition, thereby further improving the facial repair effect.

[0078] For details, please refer to Figure 3 This is a flowchart illustrating the dynamic adjustment of serum type in a facial repair system according to an embodiment of the present invention. Figure 3 As shown, the user's skin quantification data within a recent preset time period (e.g., the last 7 days) can be input into a pre-trained LSTM (Long Short-Term Memory) model to predict the trend of changes in the user's skin quantification data. If the trend of changes in the user's skin quantification data meets preset adjustment rules, the corresponding serum type for the user will be dynamically adjusted. For example, if the user's moisture content change trend over the last 7 days is greater than +15%, and the wrinkle change trend is less than -0.05mm, and the current moisture content is greater than 55%, then the user's corresponding serum type will be changed from repair and moisturizing to anti-wrinkle and plumping, while maintaining the repair of the eye area. Furthermore, based on an online learning mechanism, the model parameters of the LSTM model can be continuously updated according to the user's daily retested skin quantification data.

[0079] Based on the same inventive concept, this invention provides a facial repair method; please refer to [reference needed]. Figure 4 This is a flowchart of a facial repair method provided by an embodiment of the present invention. Figure 4As shown, the facial repair method provided by the present invention includes the following steps: Step S100, acquiring a user's facial image; Step S200, analyzing the facial image to obtain the user's facial feature data and skin quantitative index data, wherein the facial feature data includes the coordinates of multiple facial key points, and the skin quantitative index data includes barrier function data, pigmentation data, texture aging data, and water-oil balance data; Step S300, determining the user's face shape based on the user's facial feature data, and determining the corresponding repair mask model based on the user's face shape; Step S400, determining the user's skin condition type based on the user's skin quantitative index data, and determining the corresponding serum type based on the user's skin condition type.

[0080] Further, determining the user's face shape based on the user's facial feature data includes: obtaining the user's key geometric parameter data based on the user's facial feature data, the key geometric parameter data including face length, face width, mandibular angle, cheekbone height ratio, philtrum length, nose length, and cheekbone prominence; and determining the user's face shape based on the user's key geometric parameter data.

[0081] Since the facial repair method and the facial repair system provided by this invention belong to the same inventive concept, the facial repair method provided by this invention has at least all the beneficial effects of the facial repair system provided by this invention. For details, please refer to the relevant description above. Therefore, the beneficial effects of the facial repair method provided by this invention will not be elaborated here.

[0082] It should be noted that, although Figure 4 The example given is that step S300 is executed first and then step S400 is executed. However, as those skilled in the art will understand, this does not constitute a limitation of the present invention. In some other embodiments, step S400 may be executed first and then step S300 may be executed, or steps S300 and S400 may be executed simultaneously.

[0083] In some exemplary embodiments, the facial repair method provided by the present invention further includes: locating the weak areas of the user's face based on the user's skin quantitative index data, and generating a zoned repair plan based on the location results of the weak areas.

[0084] In some exemplary embodiments, the facial repair method provided by the present invention further includes: dynamically adjusting the type of serum corresponding to the user based on the trend of changes in the user's skin quantitative index data within the most recent preset time period.

[0085] It should be noted that the facial repair method and facial repair system provided by this invention are similar in technical principle, the technical problems they solve, and the technical effects they produce. Those skilled in the art can clearly understand that, for the sake of convenience and brevity, more details about the facial repair method provided by this invention can be found in the description of the facial repair system provided by this invention above, and will not be repeated here.

[0086] In summary, compared with existing technologies, the facial repair system and method provided by this invention have the following beneficial effects: This invention, by acquiring facial feature data including the coordinates of multiple key facial points, can accurately determine the user's face shape. By determining the corresponding repair mask model based on the user's face shape, it achieves precise matching between the repair mask model and the user's face shape, significantly improving the fit between the repair mask and the user's face. This avoids displacement phenomena such as edge lifting at the cheekbones or jawline suspension when the user wears the repair mask, effectively preventing problems such as localized loss of essence and uneven penetration of effective ingredients. Furthermore, by acquiring quantitative skin index data such as the user's barrier function, pigmentation, texture aging, and water-oil balance, this invention can accurately determine the user's skin condition type. By determining the corresponding essence type based on the user's skin condition type, it achieves dynamic matching between essence type and user's skin condition, effectively reducing skincare risks caused by user self-diagnosis errors and effectively improving facial repair effects.

[0087] It should be noted that the above description is only a description of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the present invention.

Claims

1. A facial repair system, characterized in that, include: The image acquisition module is configured to acquire the user's facial image; The image analysis module is configured to analyze the facial image to obtain the user's facial feature data and skin quantitative index data. The facial feature data includes the coordinates of multiple facial key points, and the skin quantitative index data includes barrier function data, pigmentation data, texture aging data, and water-oil balance data. The repair mask model matching module is configured to determine the user's face shape based on the user's facial feature data, and determine the corresponding repair mask model based on the user's face shape. as well as The serum type matching module is configured to determine the user's skin condition type based on the user's skin quantitative index data, and determine the corresponding serum type based on the user's skin condition type. Determining the user's face shape based on the user's facial feature data includes: Based on the user's facial feature data, the user's key geometric parameter data is obtained. The key geometric parameter data includes face length, face width, mandibular angle, cheekbone height ratio, philtrum length, nose length and cheekbone prominence. The user's face shape is determined based on the user's key geometric parameter data.

2. The facial repair system according to claim 1, characterized in that, The user's face length is determined based on the absolute value of the difference between the Y-axis coordinates of the key points on the forehead and the Y-axis coordinates of the key points on the chin. The user's facial width is determined based on the absolute values ​​of the Y-axis coordinates of the user's right mandibular key points and the Y-axis coordinates of the user's left mandibular key points. The angle of the user's mandibular angle is determined based on the angle between the straight line formed by the key point of the user's left mandible and the key point of the chin and the straight line formed by the key point of the user's right mandible and the key point of the chin. The cheekbone height of the user is determined based on the absolute value of the difference between the Y-axis coordinate value of the key point of the right cheekbone and the Y-axis coordinate value of the key point of the nose tip. The cheekbone height ratio of the user is determined based on the ratio of the cheekbone height to the face length. The length of the user's philtrum is determined based on the absolute value of the difference between the Y-axis coordinate value of the lower edge key point of the philtrum and the Y-axis coordinate value of the upper edge key point of the philtrum. The length of the user's nose is determined based on the absolute value of the difference between the Y-axis coordinate of the key point of the tip of the nose and the Y-axis coordinate of the key point of the bridge of the nose. The width of the user's cheekbone is determined by the absolute value of the difference between the X-axis coordinates of the key points on the right cheekbone and the left cheekbone. The cheekbone prominence is determined by the ratio of the user's cheekbone width to the width of the face.

3. The facial repair system according to claim 1, characterized in that, The key geometric parameter data also includes interpupillary distance, wherein the interpupillary distance of the user is determined based on the distance between the key points of the user's left pupil and the key points of the user's right pupil; Determining the user's face shape based on the user's key geometric parameter data includes: If the user's cheekbone height ratio is greater than 0.14 and the mandibular angle is less than 112°, or the user's face length to interpupillary distance ratio is greater than 1.75, the philtrum length to interpupillary distance ratio is less than or equal to 0.25 and the mandibular angle is less than 112°, or the user's face length to face width ratio is less than 1.35 and the cheekbone prominence is greater than 0.85, then the user's face shape is determined to be a high cheekbone round face. If the user's jaw angle is greater than or equal to 112°, or the ratio of the user's face length to face width is less than 1.40 and the cheekbone prominence is less than or equal to 0.80, then the user's face shape is determined to be a wide jaw square face. If the ratio of the user's face length to face width is greater than 1.65, or the ratio of the user's face length to interpupillary distance is greater than 1.85 and the ratio of philtrum length to interpupillary distance is greater than 0.25, or the ratio of the user's nose length to interpupillary distance is greater than 0.45 and the ratio of face length to face width is greater than 1.65, then the user's face shape is determined to be a long face.

4. The facial repair system according to claim 1, characterized in that, The step of determining the appropriate repair mask model for the user based on their face shape includes: If the user has a round face with high cheekbones, then the repair film with an extended cheekbone area will be determined as the repair film model corresponding to the user. If the user has a wide jaw and a square face, then the repair film that extends the jawline will be determined as the repair film model corresponding to the user. If the user has a long face, then the repair film that lengthens the philtrum area and widens the forehead area will be determined as the repair film model corresponding to the user.

5. The facial repair system according to claim 1, characterized in that, The barrier function data includes estimated transepidermal water loss, redness index, and skin elasticity value; the pigmentation data includes the percentage of pigmentation area, skin tone evenness index, and dark circle brightness value; the texture aging data includes the depth of crow's feet, the depth of nasolabial folds, the depth of eye wrinkles, the volume of eye bags, and the blurring of the jawline; and the water-oil balance data includes the stratum corneum moisture content and facial puffiness index.

6. The facial repair system according to claim 5, characterized in that, The step of determining the user's skin condition type based on the user's skin quantification index data includes: if the user's estimated trans-epidermal water loss value is greater than 25 g m -2 / h, the redness index is greater than 2.5, and the stratum corneum water content is less than 45%, then the user's skin state type is determined to be skin barrier impaired; If the user's crow's feet wrinkle depth is greater than 0.20mm and the skin elasticity value is less than 45, then the user's skin condition type is determined to be collagen loss. If the area of ​​the user's pigmentation spots is greater than 5.0% and the skin tone evenness index is less than 0.35, then the user's skin condition is determined to be uneven skin tone. If the user's jawline blur is greater than 15% and facial edema index is greater than 0.4, then the user's skin condition type is determined to be loose skin. If the user's eye bags are larger than 0.8cm 3 If the brightness value of dark circles is less than 35 or the depth of eye wrinkles is greater than 0.15mm, then the user's skin condition is determined to be periorbital aging.

7. The facial repair system according to claim 1, characterized in that, The step of determining the type of serum corresponding to the user based on the user's skin condition includes: If the user's skin condition is described as a damaged skin barrier, then the repair and moisturizing serum will be identified as the serum type corresponding to the user. If the user's skin condition type is collagen loss, then the anti-wrinkle plumping serum will be determined as the serum type corresponding to the user. If the user's skin condition type is uneven skin tone, then the brightening and brightening essence will be determined as the essence type corresponding to the user. If the user's skin condition type is loose skin, then the lifting and firming serum will be determined as the serum type corresponding to the user. If the user's skin condition type is periorbital aging, then the eye serum will be determined as the serum type corresponding to the user.

8. The facial repair system according to claim 1, characterized in that, The essence type matching module is also configured to: Based on the trend of changes in the user's skin quantitative index data within the most recent preset time period, the type of serum corresponding to the user is dynamically adjusted.

9. The facial repair system according to claim 1, characterized in that, The essence type matching module is also configured to: Based on the user's skin quantification index data, the weak areas on the user's face are located, and a zoned repair plan is generated based on the location results of the weak areas.

10. A facial repair method, characterized in that, include: Obtain the user's facial image; The facial image is analyzed to obtain the user's facial feature data and skin quantitative index data. The facial feature data includes the coordinates of multiple facial key points, and the skin quantitative index data includes barrier function data, pigmentation data, texture aging data, and water-oil balance data. The user's face shape is determined based on the user's facial feature data, and the corresponding repair mask model is determined based on the user's face shape. Based on the user's skin quantitative index data, determine the user's skin condition type, and based on the user's skin condition type, determine the corresponding serum type for the user; Determining the user's face shape based on the user's facial feature data includes: Based on the user's facial feature data, the user's key geometric parameter data is obtained. The key geometric parameter data includes face length, face width, mandibular angle, cheekbone height ratio, philtrum length, nose length and cheekbone prominence. The user's face shape is determined based on the user's key geometric parameter data.

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