Object state detection and prompting method, device, dressing mirror and program product

Abstract

The application relates to a method and device for detecting and prompting a state of an object, a dressing mirror and a program product. The method comprises the following steps: obtaining first sebum secretion data of a target part of an object to be detected according to a part image of the target part acquired by the dressing mirror; the target part at least includes a face and a head; obtaining second sebum secretion data of the target part according to a capacitance value of the target part acquired by the dressing mirror; determining a cleaning state of the target part of the object to be detected based on the first sebum secretion data and the second sebum secretion data; generating prompt information for the object to be detected based on the cleaning state, and displaying the prompt information on the dressing mirror. The method can improve the detection accuracy of the cleaning state and provide personalized prompt information for the cleaning state of the object to be detected.

Description

Technical Field

[0001] This application relates to the field of smart home technology, and in particular to a method, device, vanity mirror, and program product for detecting and indicating the state of an object. Background Technology

[0002] In the early stages of vanity mirror technology development, users primarily relied on ordinary flat mirrors for makeup and skincare. With advancements in optical technology, vanity mirrors began integrating fill light and adjustable lighting functions to adapt to different lighting conditions. Later, with the rapid development of artificial intelligence, vanity mirror technology is evolving towards ecosystem integration and personalization, offering users intelligent makeup, skin analysis, and other entertainment content.

[0003] However, as a daily grooming tool, vanity mirrors are currently used primarily by users to observe the cleanliness of their appearance with their naked eyes, making it impossible to objectively quantify and judge the cleanliness of the user's appearance. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, device, vanity mirror, computer-readable storage medium, and computer program product for detecting and prompting about the state of an object, which can improve the accuracy of judging the cleanliness of the object to be detected and provide corresponding prompts.

[0005] Firstly, this application provides a method for detecting and indicating the state of an object. The method includes:

[0006] Based on the image of the target area of ​​the subject obtained through a vanity mirror, the first sebum secretion data of the target area is obtained; the target area includes at least the face and head of the subject.

[0007] Based on the capacitance value of the target area obtained through the dressing mirror, the second sebum secretion data of the target area is obtained;

[0008] Based on the first oil secretion data and the second oil secretion data, the cleanliness status of the target area of ​​the object to be tested is determined;

[0009] Based on the cleanliness status, a prompt message is generated for the object to be detected, and the prompt message is displayed on the vanity mirror.

[0010] In one embodiment, determining the cleanliness status of the target area of ​​the object to be tested based on the first sebum secretion data and the second sebum secretion data includes:

[0011] Based on the temperature and humidity data of the environment in which the object to be tested is located, the first oil secretion data, and the second oil secretion data, the target oil secretion data of the target location is obtained.

[0012] If the target sebum secretion data exceeds the preset sebum secretion threshold, then the cleanliness of the target part of the object to be tested is confirmed to be substandard.

[0013] If the target sebum secretion data does not exceed the sebum secretion threshold, then the cleanliness of the target area of ​​the object to be tested is confirmed to be up to standard.

[0014] In one embodiment, target sebum secretion data of the target location is obtained based on temperature and humidity data of the environment in which the object to be detected is located, the first sebum secretion data, and the second sebum secretion data, including:

[0015] The first and second sebum secretion data are fused to obtain candidate sebum secretion data for the target site.

[0016] Based on the temperature and humidity data of the environment in which the object to be tested is located, the candidate oil secretion data is corrected to obtain the target oil secretion data of the target location.

[0017] In one embodiment, based on the cleaning status, a prompt message is generated for the object to be detected, including:

[0018] The historical sebum secretion data of the target area in a historical time period is input into the sebum secretion prediction model corresponding to the object to be detected, so as to obtain the predicted sebum secretion data of the target area in the current time period.

[0019] Based on the difference between the target sebum secretion data and the predicted sebum secretion data, a sebum change alert is generated for the target area.

[0020] Based on the basic prompt information corresponding to the target sebum secretion data and the sebum change prompt information, prompt information is generated for the target area.

[0021] In one embodiment, after displaying the prompt message on the vanity mirror, the method further includes:

[0022] Obtain the lighting data of the environment in which the dressing mirror is located;

[0023] Based on the illumination data and the prompt information, determine the target illumination parameters of the dressing mirror's lighting module;

[0024] The dressing mirror is controlled to adjust the current lighting parameters of the lighting module to the target lighting parameters.

[0025] In one embodiment, based on a region image of the target region of the object to be detected obtained through a vanity mirror, first sebum secretion data of the target region is obtained, including:

[0026] The image of the area is processed to extract oil features, thereby obtaining the oil features of the target area; the image of the area is obtained by capturing the target area at the target wavelength provided by the dressing mirror.

[0027] The image of the area is subjected to light reflection analysis to obtain the reflective features of the target area; the reflective features are used to characterize the optical signals reflected by the target area.

[0028] Based on the oil characteristics and the reflective characteristics, the first oil secretion data of the target area is obtained.

[0029] In one embodiment, second sebum secretion data of the target area is obtained based on the capacitance value of the target area acquired through the vanity mirror, including:

[0030] When the capacitive sensor of the vanity mirror is in continuous contact with the target area for a preset time, the capacitance value of the target area within the preset time is obtained through the capacitive sensor.

[0031] Based on the change in capacitance value within the preset time period, the second sebum secretion data of the target area is obtained.

[0032] Secondly, this application also provides an object status detection and notification device. The device includes:

[0033] The first oil detection module is used to obtain first oil secretion data of the target area based on the area image of the target area of ​​the object to be detected obtained through a dressing mirror; the target area includes at least the face and head of the object to be detected.

[0034] The second oil detection module is used to obtain the second oil secretion data of the target area based on the capacitance value of the target area obtained through the dressing mirror;

[0035] A cleanliness status determination module is used to determine the cleanliness status of the target area of ​​the object to be tested based on the first oil secretion data and the second oil secretion data.

[0036] The prompt information display module is used to generate prompt information for the object to be tested based on the cleaning status, and display the prompt information on the dressing mirror.

[0037] Thirdly, this application also provides a dressing mirror. The dressing mirror includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0038] Based on the image of the target area of ​​the subject obtained through a vanity mirror, the first sebum secretion data of the target area is obtained; the target area includes at least the face and head of the subject.

[0039] Based on the capacitance value of the target area obtained through the dressing mirror, the second sebum secretion data of the target area is obtained;

[0040] Based on the first oil secretion data and the second oil secretion data, the cleanliness status of the target area of ​​the object to be tested is determined;

[0041] Based on the cleanliness status, a prompt message is generated for the object to be detected, and the prompt message is displayed on the vanity mirror.

[0042] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0043] Based on the image of the target area of ​​the subject obtained through a vanity mirror, the first sebum secretion data of the target area is obtained; the target area includes at least the face and head of the subject.

[0044] Based on the capacitance value of the target area obtained through the dressing mirror, the second sebum secretion data of the target area is obtained;

[0045] Based on the first oil secretion data and the second oil secretion data, the cleanliness status of the target area of ​​the object to be tested is determined;

[0046] Based on the cleanliness status, a prompt message is generated for the object to be detected, and the prompt message is displayed on the vanity mirror.

[0047] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0048] Based on the image of the target area of ​​the subject obtained through a vanity mirror, the first sebum secretion data of the target area is obtained; the target area includes at least the face and head of the subject.

[0049] Based on the capacitance value of the target area obtained through the dressing mirror, the second sebum secretion data of the target area is obtained;

[0050] Based on the first oil secretion data and the second oil secretion data, the cleanliness status of the target area of ​​the object to be tested is determined;

[0051] Based on the cleanliness status, a prompt message is generated for the object to be detected, and the prompt message is displayed on the vanity mirror.

[0052] The aforementioned object status detection and prompting method, device, vanity mirror, storage medium, and computer program product obtain first sebum secretion data of the target area based on a part image of the target area of ​​the object to be detected obtained through the vanity mirror; the target area includes at least the face and head; second sebum secretion data of the target area is obtained based on the capacitance value of the target area obtained through the vanity mirror; the cleanliness status of the target area of ​​the object to be detected is determined based on the first and second sebum secretion data; and prompting information for the object to be detected is generated based on the cleanliness status and displayed on the vanity mirror. This method utilizes a vanity mirror to integrate image acquisition and capacitive sensing for dual detection. First and second sebum secretion data are acquired from target areas, including the face and head, of the subject. Through multi-dimensional data fusion analysis, the cleanliness status of the target areas is accurately determined. Based on this cleanliness status, prompts are generated and displayed on the vanity mirror. This not only achieves multi-dimensional and precise quantitative monitoring of facial and scalp oil production, effectively improving the accuracy and reliability of cleanliness status judgment, but also provides personalized prompts tailored to the subject's actual cleanliness needs. Subjects can intuitively and promptly grasp the cleanliness status of their face and scalp, assisting them in making scientific cleanliness and care decisions. The entire detection and prompting process can be completed using a vanity mirror without the need for additional professional testing equipment. In addition to improving the accuracy of cleanliness status detection, it also significantly enhances the convenience for subjects to check their cleanliness status, making it a convenient vanity mirror for use in vehicles. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart illustrating an object state detection and notification method in one embodiment;

[0055] Figure 2 This is a schematic diagram of the structure of a dressing mirror in one embodiment;

[0056] Figure 3 This is a flowchart illustrating the steps for generating prompt information for an object to be detected in one embodiment;

[0057] Figure 4 This is a flowchart illustrating an object state detection and notification method in one embodiment;

[0058] Figure 5 This is a flowchart illustrating an object state detection and notification method in one embodiment;

[0059] Figure 6 This is a structural block diagram of an object state detection and prompting device in one embodiment;

[0060] Figure 7 This is a diagram of the internal structure of a dressing mirror in one embodiment. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0062] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0063] In one embodiment, such as Figure 1 As shown, a method for detecting and prompting the state of an object is provided. This embodiment illustrates the method by applying it to a dressing mirror, but it can also be applied to a system including a terminal and a dressing mirror, and is implemented through the interaction between the terminal and the dressing mirror. In this embodiment, the method includes the following steps:

[0064] Step S101: Based on the image of the target area of ​​the subject to be tested obtained through the dressing mirror, obtain the first oil secretion data of the target area; the target area includes at least the face and head of the subject to be tested.

[0065] The object to be tested refers to the object whose cleanliness is being checked using a vanity mirror. For example, the object to be tested could be a person.

[0066] In this context, the target area refers to a body part of the subject to be inspected. In this application, the cleanliness of the subject is inspected using a vanity mirror; therefore, the target area includes at least the face and head of the subject.

[0067] Among them, sebum secretion data (including first sebum secretion data and second sebum secretion data) refers to data describing the amount of sebum secreted, the area of ​​sebum secretion, and other sebum secretion conditions of the target area.

[0068] Figure 2 This is a structural diagram of a dressing mirror, such as... Figure 2 As shown, the vanity mirror 200 includes a mirror module 201, an intelligent recognition module 202, a data processing module 203, a display module 204, a light module 205, a control module 206, and a power module 207. The structural components and their connections are shown below:

[0069] (1) Mirror module: including mirror body 2001 and mirror frame 2002. The mirror body is located in the core area in the center of the mirror frame and is fixedly connected to the mirror frame. The mirror body can be a high-definition reflective mirror for daily observation of the object to be detected, and at the same time provides the imaging basis for the intelligent recognition module.

[0070] (2) Intelligent recognition module: integrates camera (such as high-definition camera, 3D camera) and sensor (such as capacitive sensor or miniature capacitive sensor, temperature and humidity sensor). The camera is installed on the upper edge of the frame and the shooting angle of the camera is adjustable; the sensor can be installed on the left and right sides of the frame close to the mirror body; the intelligent recognition module is connected to the data processing module by wired or wireless means to collect images and status data (such as oil secretion data, cleanliness characteristics, etc.) of the face and head of the object to be detected.

[0071] (3) Data processing module: including processor (e.g., a microprocessor can be used); the data processing module is located at the lower edge of the frame and inside the frame; the data processing module is connected to the intelligent recognition module, the display module and the control module respectively, receives the data collected by the intelligent recognition module, processes the data through preset algorithms (such as image recognition algorithm, oil content analysis algorithm), and judges the cleanliness of the object to be tested based on oil secretion data such as facial oil production and head oil production;

[0072] (4) Display module: including display screen; the display screen is a transparent display screen; the display module is attached to the inside of the mirror module and connected to the data processing module to display prompt information;

[0073] (5) Lighting module: including LED (Light Emitting Diode) lamp beads; the lighting module is installed around the inside of the frame; the lighting module is connected to the control module, and the brightness and color temperature can be adjusted to provide suitable light for the object to be detected, and also to provide light illumination for the intelligent recognition module, so that the image collected by the intelligent recognition module is clearer and more distinct;

[0074] (6) Control module: including switch assembly; the control module is connected to the data processing module and the lighting module, receives instructions from the data processing module, controls the working state of the lighting module, and can also receive manual operation instructions from the object to be detected (such as switch instructions, mode switching instructions); the control module is located inside the right side of the mirror frame, and the switch assembly can partially protrude outside the mirror frame;

[0075] (7) Power module: Located at the bottom rear of the frame, it is electrically connected to all power modules (including intelligent recognition module, data processing module, display module, lighting module and control module).

[0076] In practical applications, vanity mirrors can be installed in easily accessible locations within the vehicle. For example, they can be installed behind the driver's seat for rear passengers, or on the side of the driver's or passenger's seat for their convenience. Vanity mirrors can also be detachable, such as the mirror inside the sun visor in front of the driver or passenger, further enhancing the ease of use for those being inspected within the vehicle.

[0077] For example, after the object to be detected activates the cleanliness detection function of the vanity mirror by manually triggering the control module (such as a switch component) or through voice interaction, the vanity mirror's data processing module automatically detects whether the object to be detected is within a preset distance range of the vanity mirror based on the data collected by the intelligent recognition module. If the object to be detected is detected within the preset distance range of the vanity mirror, the data processing module controls the light module to enter the shooting mode. In the shooting mode, the light module emits light of the target wavelength to illuminate the object to be detected. The camera in the intelligent recognition module captures images of the target parts of the object under the light of the target wavelength. If multiple target parts of the object to be detected need to be detected (such as the face and head of the object to be detected), images of multiple target parts can be captured. Then, the data processing module analyzes the images of the target parts using image recognition algorithms to analyze whether there is oil secretion in the target parts, as well as the area and amount of oil secretion in the target parts, thereby obtaining the first oil secretion data of the target parts.

[0078] Step S102: Based on the capacitance value of the target area obtained through the vanity mirror, the second sebum secretion data of the target area is obtained.

[0079] For example, a contactable miniature capacitive sensor can be installed on the left (or right) side of the frame of a vanity mirror, close to the mirror body. When the target area of ​​the object to be detected comes into contact with the miniature capacitive sensor, the sensor detects the capacitance value of the target area within a preset time period. It should be noted that the capacitance value of the target area changes due to the presence of oil (oil in the target area is an insulator, while oil-free skin has a certain degree of conductivity; the presence of oil and the amount of oil secretion will cause changes in the capacitance value of the target area). Therefore, the data processing module can analyze the change in capacitance value within a preset time period (e.g., 3 seconds, 5 seconds, etc.) to determine whether oil secretion exists in the target area, as well as the area and amount of oil secretion, thereby obtaining second oil secretion data for the target area.

[0080] Step S103: Based on the first oil secretion data and the second oil secretion data, determine the cleanliness status of the target area of ​​the object to be tested.

[0081] Among them, cleanliness status refers to information reflecting whether the cleanliness of the target area meets the standards.

[0082] For example, the data processing module integrates the first sebum secretion data and the second sebum secretion data to obtain the target sebum secretion data of the target area; compares the target sebum secretion data with a preset sebum secretion threshold to obtain the comparison result between the target sebum secretion data and the sebum secretion threshold, and judges whether the cleanliness of the target area meets the standard based on the comparison result.

[0083] Step S104: Based on the cleanliness status, generate a prompt message for the object to be tested and display the prompt message on the vanity mirror.

[0084] The prompt information refers to the information that prompts the object to be tested to perform cleaning and care.

[0085] For example, if the cleanliness of the target area is satisfactory, it means that the target area of ​​the subject has low oil secretion and good cleanliness. In this case, a prompt message corresponding to the satisfactory cleanliness, such as "You look good today, enjoy your day," can be generated. If the cleanliness of the target area is unsatisfactory, it means that the target area of ​​the subject has excessive oil secretion. In this case, a prompt message corresponding to the unsatisfactory cleanliness, such as "Your face is oily; it is recommended to use a gentle cleansing tool to clean your face," or "Your hair is slightly oily; it is recommended to wash it to keep it clean and fresh," can be generated. For example, a text generation model can be used to generate prompt messages corresponding to the cleanliness status, or multiple preset prompt messages stored in a prompt message library can be retrieved. The data processing module sends the prompt message to the display module for display. The display module is located in a specific area of ​​the vanity mirror and will not obstruct the subject's daily grooming activities.

[0086] In practical applications, the prompts can also provide more detailed cleaning suggestions, such as recommending the type of cleaning products. The data processing module can provide personalized cleaning cycle recommendations based on the historical sebum secretion data of the object being tested.

[0087] In addition to the transparent display screen, the display module can also be set as a projection device to project the prompt information onto the surface of the mirror body, which can also realize the information display function.

[0088] In the aforementioned method for detecting and alerting the state of an object, a vanity mirror is used to integrate image acquisition and capacitive sensing for dual detection. First and second sebum secretion data are acquired for the target areas of the object to be detected, including the face and head. Through multi-dimensional data fusion analysis, the cleanliness status of the target areas is accurately determined, and alert information is generated and displayed on the vanity mirror based on this cleanliness status. This not only achieves multi-dimensional and accurate quantitative monitoring of facial and scalp oil production, effectively improving the accuracy and reliability of cleanliness status judgment, but also provides personalized alerts tailored to the actual cleanliness needs of the object to be detected. This allows the object to intuitively and promptly grasp the cleanliness status of their face and scalp, helping them make scientific cleanliness and care decisions. The entire detection and alerting process can be completed using a vanity mirror without the need for additional professional detection instruments, greatly improving the convenience of detecting the cleanliness status of the object to be detected. It can also be conveniently used as a vanity mirror in a car.

[0089] In one embodiment, step S103 above, based on the first oil secretion data and the second oil secretion data, determines the cleanliness status of the target area of ​​the object to be tested, specifically including the following: obtaining the target oil secretion data of the target area based on the temperature and humidity data of the environment where the object to be tested is located, the first oil secretion data, and the second oil secretion data; if the target oil secretion data exceeds a preset oil secretion threshold, then the cleanliness status of the target area of ​​the object to be tested is confirmed to be substandard; if the target oil secretion data does not exceed the oil secretion threshold, then the cleanliness status of the target area of ​​the object to be tested is confirmed to be compliant.

[0090] For example, the temperature and humidity sensor of the intelligent identification module collects the temperature and humidity data of the environment in which the object to be detected is currently located, and sends the temperature and humidity data to the data processing module. The data processing module performs data correction processing on the first and second oil secretion data based on the temperature and humidity data of the environment in which the object to be detected is located. For example, high temperature and high humidity environments accelerate the rate of oil production in the human body, while low temperature and low humidity environments slow down the rate of oil production. Therefore, the same oil production value actually represents different cleanliness levels under the same temperature and humidity data. Therefore, this application also utilizes temperature and humidity data to correct the baseline value of oil secretion under different environmental climates to improve the adaptability and accuracy of the processed target oil secretion data to the scene.

[0091] The data processing module compares the target sebum secretion data with a preset sebum secretion threshold. If the target sebum secretion data exceeds the threshold (i.e., target sebum secretion data > threshold), the cleanliness of the target area is deemed substandard. Conversely, if the target sebum secretion data does not exceed the threshold (i.e., target sebum secretion data ≤ threshold), the cleanliness of the target area is deemed satisfactory. In addition to threshold comparison, machine learning models can also be used to determine cleanliness. For example, the target sebum secretion data can be input into a machine learning model, which can then analyze the cleanliness of the target area.

[0092] In this embodiment, the temperature and humidity data of the environment in which the object to be tested is located are integrated with the first oil secretion data obtained by optical detection and the second oil secretion data obtained by capacitive sensing in a multi-dimensional process to obtain the target oil secretion data of the target area. By comparing the target oil secretion data with the preset oil secretion threshold, the cleanliness status of the target area can be accurately determined. The temperature and humidity data can be used to make the target oil secretion data more in line with the actual oil production status of the environment, which can basically offset the influence of different climatic conditions such as high temperature and high humidity, low temperature and low humidity on the oil secretion status. This can eliminate the misjudgment of cleanliness status caused by environmental differences as much as possible, and greatly improve the scene adaptability and accuracy of the target oil secretion data. This makes the judgment result of cleanliness status more in line with the actual skin and scalp status of the object to be tested in different environments, and provides a scientific and accurate judgment basis for generating personalized cleaning and care prompts.

[0093] In one embodiment, the first sebum secretion data and the second sebum secretion data are fused to obtain the target sebum secretion data of the target area. Specifically, this includes: fusing the first sebum secretion data and the second sebum secretion data to obtain candidate sebum secretion data of the target area; and correcting the candidate sebum secretion data based on the temperature and humidity data of the environment in which the object to be detected is located to obtain the target sebum secretion data of the target area.

[0094] Among them, temperature and humidity data refer to the temperature and humidity values ​​of the environment.

[0095] For example, the data processing module can fuse the first and second sebum secretion data using feature-level fusion technology. For instance, it can extract core features from the first sebum secretion data (optical): such as regional features of sebum distribution (proportion of oily areas like the T-zone / nasal wings) and density features (local sebum density); and extract core features from the second sebum secretion data (capacitance): such as the rate of capacitance change (rate of increase / decrease in capacitance value within a preset contact time) and steady-state features (final stable value of capacitance). A feature fusion model is then established, inputting the regional and density features of sebum distribution, as well as the rate and steady-state features of capacitance change, into the model. The feature fusion model outputs a fused feature set using preset rules (such as feature matching and feature weighting), and then transforms the fused feature set into unified candidate sebum secretion data. Feature-level fusion technology first extracts the core features of the first and second sebum secretion data, then fuses these core features to generate candidate sebum secretion data. This reduces the loss of original detection features during numerical normalization and better preserves the original information from two significantly different detection methods.

[0096] The data processing module can also fuse the first and second sebum secretion data through standardization, weighted summation, and other techniques. For example, the original detection units and data ranges of the first (optical) and second (capacitive) sebum secretion data are different (e.g., optical data is represented by "sebum distribution percentage / 0-100 quantization value," while capacitive data is represented by "capacitance change (μF or its converted sebum secretion level)"). Therefore, firstly, a normalization algorithm is used to set the first and second sebum secretion data to the same numerical range (e.g., 0-100), unifying them as "sebum secretion amount," making the two data sets comparable and computable. Then, based on the preset weights corresponding to the first and second sebum secretion data, a weighted summation is performed on the first and second sebum secretion data to calculate the candidate sebum secretion data. Standardization and weighted summation techniques can determine the candidate sebum secretion data according to the importance of different scenarios and detection methods.

[0097] The data processing module can pre-establish the correlation between temperature and humidity and the correction coefficient of sebum secretion; based on the correlation, it determines the target correction coefficient corresponding to the temperature and humidity data; and through the target correction coefficient, it performs linear weighted adjustment processing on the candidate sebum secretion data to calculate the target sebum secretion data of the target location.

[0098] In this embodiment, the first oil secretion data obtained through optical detection and the second oil secretion data obtained through capacitive sensing are initially fused. Then, the candidate oil secretion data are corrected by combining the temperature and humidity data of the environment in which the object to be tested is located. By using the influence of temperature and humidity data on the rate of oil secretion in the human body, the scene interference caused by different in-vehicle environmental conditions such as high temperature and high humidity, low temperature and low humidity on oil secretion detection is corrected. This makes the target oil secretion data obtained after correction combine the advantages of optical imaging's full-area detection and the advantages of capacitive sensing's close-range accurate detection, and it can also closely match the actual environmental state of the object to be tested. This greatly improves the accuracy, objectivity and scene adaptability of the target oil secretion data, and lays the foundation for subsequent accurate determination of the cleanliness status of the target area and generation of personalized care tips.

[0099] In one embodiment, such as Figure 3 As shown, in step S104 above, based on the cleaning status, a prompt message is generated for the object to be detected, specifically including the following:

[0100] Step S301: Input the historical sebum secretion data of the target area in the historical time period into the sebum secretion prediction model corresponding to the object to be detected, and obtain the predicted sebum secretion data of the target area in the current time period.

[0101] Among them, the sebum secretion prediction model refers to the model used to predict the sebum secretion data of the target area in the next time period (i.e., predict sebum secretion data).

[0102] Historical sebum secretion data refers to a series of actual sebum secretion data of the target area of ​​the object to be tested within a historical time period.

[0103] For example, such as Figure 2 As shown, the vanity mirror also includes a storage module 208 connected to the data processing module. It can also set an object identifier for the object to be detected, and record historical sebum secretion data of the target area of ​​the object within a historical time period based on the object identifier. For example, it can record daily facial and hair condition data of the object to be detected, forming a care profile for the object; the historical sebum secretion data is stored in the storage module. The data processing module uses the historical sebum secretion data to train a personalized sebum secretion model for the object to be detected.

[0104] The data processing module inputs the historical sebum secretion data of the target part of the object to be detected into the sebum secretion prediction model corresponding to the object to be detected. The sebum secretion prediction model predicts the sebum secretion data of the target part in the current time period based on the learned sebum secretion pattern of the object to be detected.

[0105] Step S302: Based on the difference between the target sebum secretion data and the predicted sebum secretion data, generate sebum change prompt information for the target area.

[0106] For example, the data processing module calculates the difference between the target sebum secretion data and the predicted sebum secretion data of the object to be tested. Based on the difference, it determines the sebum secretion change information of the target area. For instance, assuming the difference is "actual sebum secretion is 20% higher than predicted," the sebum secretion change information could be an upward trend. Or, assuming the difference is "actual sebum secretion is 15% lower than predicted," the sebum secretion change information could be a decrease. Then, based on the sebum secretion change information, it generates sebum change prompts for the target area, using enamel change prompts to indicate whether the current sebum secretion of the target area of ​​the object deviates from its trend.

[0107] Step S303: Based on the basic prompt information and oil change prompt information corresponding to the target oil secretion data, generate prompt information for the target area.

[0108] For example, the data processing module can first generate basic prompt information based on the target sebum secretion data (this is the most core basic prompt, such as "cleanliness status meets the standard, sebum secretion is normal" or "cleanliness status does not meet the standard, there is a lot of sebum residue"); then integrate the basic prompt information and the sebum change prompt information to finally generate a final prompt information that takes into account both the "current status" and the "change trend", providing a more complete reference for the object to be tested.

[0109] In this embodiment, historical sebum secretion data of the target area of ​​the object to be detected is input into the sebum secretion prediction model to obtain predicted sebum secretion data for the current time period. Sebum change alerts are generated by combining the difference between the measured target sebum secretion data and the predicted sebum secretion data. These alerts are then integrated with the basic alerts corresponding to the target sebum secretion data to generate the final target area alert. This upgrade from "single current sebum secretion data detection and alerts" to "personalized comprehensive alerts combining historical patterns and trend predictions" not only relies on historical data and the prediction model to uncover the sebum secretion patterns of the object to be detected, making the judgment of sebum change trends more closely aligned with the individual characteristics of the object, but also utilizes the difference... The analysis intuitively reflects the deviation between current sebum secretion and predicted patterns, presenting the dynamic changes in the oily state of the tested object. It integrates basic state information and sebum change information to generate final alerts, allowing the tested object to clearly understand the current cleanliness and actual oil production of the target area, while also gaining timely insight into the changing trends of their sebum secretion. This ensures the alerts are both objectively state-based and trend-guided, significantly enhancing their richness, personalization, and practicality. It elevates skin and hair oil monitoring from simple numerical detection and state judgment to a more valuable personalized skincare and haircare reference, providing comprehensive and accurate data for developing targeted cleansing, oil control, and skincare / haircare plans for the tested object.

[0110] In one embodiment, after displaying the prompt information on the vanity mirror, step S104 further includes: acquiring the lighting data of the environment where the vanity mirror is located; determining the target lighting parameters of the vanity mirror's lighting module based on the lighting data and the prompt information; and controlling the vanity mirror to adjust the current lighting parameters of the lighting module to the target lighting parameters.

[0111] For example, the smart recognition module uses sensors (such as photosensors) to acquire current lighting data of the environment in which the vanity mirror is located (e.g., indoor environments like bedrooms and bathrooms, or outdoor environments like grass and campsites). This lighting data includes, but is not limited to, data on light intensity and color temperature. The data processing module then handles the lighting. The prompts are the content the object being monitored is about to see, and the object may perform cleaning operations based on these prompts. Therefore, the vanity mirror's lighting must not only adapt to the environment but also ensure that the prompts are clearly displayed and that the object can clearly observe the oiliness of the target area. Thus, the ambient lighting information is combined with the previously generated oil monitoring prompts to jointly determine the target lighting parameters for the mirror's lighting module. For instance, a mapping relationship between the type of lighting data and prompts and the lighting parameters can be pre-established. Then, the data processing module can obtain the target lighting parameters corresponding to the currently established lighting data and the type of prompts based on this mapping relationship. Once the target lighting parameters are determined, the data processing module can automatically control the lighting module of the vanity mirror to adjust the current lighting parameters, such as brightness and color temperature, to the newly determined target lighting parameters. The entire process requires no manual adjustment by the object being tested, achieving adaptive linkage of the lighting.

[0112] For example, in low-light conditions at night, if the message "T-zone cleansing is inadequate, excessive oil residue" is displayed, the vanity mirror will adjust the light to a moderate brightness plus warm light, which avoids glare from strong light and allows the subject to clearly see the oily areas of the T-zone; during the day near a bright window, the light brightness will be increased and adjusted to cool light to counteract ambient reflections and ensure that the message and facial details are clearly visible.

[0113] In this embodiment, by acquiring the ambient light data of the dressing mirror's environment and combining it with the corresponding prompts for oil detection, the target lighting parameters of the lighting module are determined. The lighting module is then automatically controlled to adjust the current parameters to the target parameters, achieving dual adaptive linkage between the dressing mirror's lighting and ambient light and oil detection prompts. This not only relies on ambient light data to ensure that the lighting parameters are accurately adapted to the current ambient light conditions, effectively avoiding visual discomfort caused by strong light reflections or dim lighting in the vehicle's interior environment, but also optimizes the lighting parameters based on the display and usage requirements of the prompts, ensuring that the prompts are clearly visible and that the subject can more clearly observe target areas such as the face and scalp, thus balancing the visual needs of prompt viewing with the clarity of area observation.

[0114] In one embodiment, step S101, which obtains the first sebum secretion data of the target area based on the area image of the target area of ​​the object to be detected obtained through the dressing mirror, specifically includes the following: performing sebum feature extraction processing on the area image to obtain the sebum features of the target area; the area image is obtained by acquiring the target area at the target wavelength provided by the dressing mirror; performing light reflection analysis processing on the area image to obtain the reflective features of the target area; the reflective features are used to characterize the optical signals reflected by the target area; and obtaining the first sebum secretion data of the target area based on the sebum features and the reflective features.

[0115] For example, the data processing module of the dressing mirror controls the light module to emit light of the target wavelength (such as ultraviolet light or polarized light) to illuminate the target area (such as the face or head). The data processing module calls the high-resolution camera of the intelligent recognition module (such as the dressing mirror) to capture an image of the target area under the light source of the target wavelength, for example, by using a camera located above the dressing mirror to photograph the target area and obtain an image of the area.

[0116] The data processing module receives the body part image sent by the intelligent recognition module and performs oil feature extraction processing on the body part image. This can be done by using image recognition algorithms to extract features such as color blocks, regions, and textures corresponding to oil in the body part image, thereby obtaining the oil features of the target body part. For example, oil usually has high reflectivity, which appears as higher brightness in the image. For instance, oily areas of skin will be brighter than normal skin, and the color of oily areas will be more yellow (or whiter) than the surrounding skin. The texture of oily areas will be smoother, and the edges of oily areas will be more blurred and softer, while the edges of non-oily areas will be clearer and sharper. Oily areas are mostly irregular connected regions (clumps, diffused) rather than isolated points. Based on this, image recognition algorithms can be used to calculate the brightness value, gray value, color channel, texture, area of ​​connected regions, and edge sharpness of each pixel in the body part image. Then, the gray value and color channel are used to distinguish the color blocks of oil, and the brightness value, area of ​​connected regions, and edge sharpness are used to distinguish oily areas and non-oily areas. The data processing module also performs light reflection analysis on the part image to capture the light signals reflected back from the target part in the part image and convert them into reflective features (for example, reflective features can include reflectivity, i.e., the intensity of the reflected light signal). These reflective features can reflect information such as the intensity and range of light reflected by grease. For example, based on the brightness channel of the part image, reflective regions can be segmented. In simple scenarios, binarization and connected component analysis can be used to filter noise and locate effective reflective regions in the part image. In complex scenarios, a semantic segmentation model can be used to achieve pixel-level accurate segmentation, ultimately obtaining a reflective region mask for the part image. By calculating the mean light intensity, light intensity distribution, and light intensity gradient of pixels within the reflective region (or reflective region mask), the light signal (i.e., the light signal reflected back from the target part) of the reflective region (or reflective region mask) is quantified. Based on the light signal, reflective features such as the peak light intensity, coefficient of variation of light intensity, and light intensity skewness of the light signal in the reflective region are calculated. The data processing module can use oil features to identify the distribution area and density of oil on target sites, and use reflective features to assist in verifying the presence, distribution area, and amount of oil on target sites. It can then perform a comprehensive analysis by combining the oil analysis results obtained based on oil features and those obtained based on reflective features. For example, it can use the oil analysis results obtained based on oil features as the primary indicator and the results obtained based on reflective features as a secondary indicator, and use the results obtained based on reflective features to correct the results obtained based on oil features. Alternatively, it can input the oil analysis results obtained based on oil features and those obtained based on reflective features into a sebum secretion prediction model based on machine learning or deep learning to predict sebum secretion data, and finally obtain quantifiable first sebum secretion data (such as the specific amount and grade of sebum secretion).

[0117] Taking the head as an example, the head includes the hairline, crown, scalp, and hair. Images of the head are captured from multiple angles using a camera. The presence of sebum secretion on the head is identified by the oil characteristics of the images, such as the presence of obvious oil stains or dandruff accumulation. Then, the reflective characteristics of the images are combined to further verify the presence of sebum secretion on the head, and the area and amount of sebum secretion are calculated to obtain the first sebum secretion data of the head, which reflects the sebum accumulation on the head.

[0118] Taking the face as an example, which includes areas such as the forehead, nose, and cheeks, images of facial areas are captured from multiple angles using a camera. Similar to the head, the presence of oil secretion on the face is identified by the oil characteristics of the images of these areas, such as the presence of obvious oil stains. Then, the reflective characteristics of the images of these areas are combined to further verify whether there is oil secretion on the head, such as whether the nose and cheeks are oily and reflective. The area and amount of oil secretion are calculated to obtain the first oil secretion data of the face, which reflects the oil accumulation on the face.

[0119] In addition, the intelligent recognition module can also be equipped with a spectral analysis sensor. The spectral analysis sensor can determine the oil content and cleanliness by analyzing the spectrum reflected from the face and hair, rather than relying on a combination of image recognition and oil sensor.

[0120] In this embodiment, an intelligent recognition module acquires images of the target area under light irradiation at the target wavelength. A data processing module then extracts oil features and analyzes light reflection from these images, obtaining oil features that visually represent the state of the oil itself and reflective features that characterize the optical reflective properties of the oil. Based on the fusion analysis of these two types of features, the first oil secretion data for the target area is obtained. This dual-feature collaborative analysis enables precise quantitative calculation of the oil secretion data, effectively avoiding the identification bias that can easily occur with single-feature analysis. Furthermore, the introduction of the optical reflective properties of the reflective features improves the accuracy of oil secretion calculation, thereby effectively enhancing the detection accuracy and reliability of the first oil secretion data. This detection method utilizes a vanity mirror, eliminating the need for complex professional operations and allowing for convenient use as a car vanity mirror. It balances detection accuracy with ease of use, providing high-quality oil data support for accurate subsequent determination of cleanliness.

[0121] In one embodiment, step S102, which obtains the second sebum secretion data of the target area based on the capacitance value of the target area obtained through the vanity mirror, specifically includes the following: when the capacitive sensor of the vanity mirror is in continuous contact with the target area for a preset time, the capacitance value of the target area within the preset time is obtained through the capacitive sensor; and the second sebum secretion data of the target area is obtained based on the change in the capacitance value within the preset time.

[0122] For example, a contact area can be set on the outside of the vanity mirror, or a separate contact area can be set up and a communication connection (such as Bluetooth, wireless network, etc.) established between the contact area and the vanity mirror to transmit the collected capacitance value to the vanity mirror. A miniature capacitance sensor is integrated into the contact area. When the target part of the object to be detected is in continuous contact with the miniature capacitance sensor of the vanity mirror for a preset time (instantaneous contact can collect a small amount of capacitance data, which can easily lead to inaccurate analysis results; for example, a user can contact the miniature capacitance sensor with their forehead or scalp for 3, 4, or 5 seconds), the capacitance sensor will continuously collect the capacitance value of the target part, obtaining continuous capacitance values ​​within the preset time, and sending these continuous capacitance values ​​within the preset time to the data processing module. In practical applications, the vanity mirror can be installed in a convenient location inside the vehicle, for example, the mirror inside the sun visor in front of the driver or passenger can be set as a detachable vanity mirror, facilitating continuous contact between the object to be detected and the contact area of ​​the vanity mirror. In addition, capacitance values ​​of the target part can also be collected through capacitance sensors mounted on other devices linked to the vanity mirror.

[0123] The data processing module calculates the change in capacitance value over a preset time period (e.g., the amplitude of capacitance fluctuation, the difference between rise and fall, the average rate of change, etc.). This change is crucial for characterizing the state of sebum secretion because sebum is an insulator. When the capacitive sensor is in continuous contact with the skin, the sebum gradually adheres to the sensor surface. The continuous change in dielectric properties leads to continuous fluctuations in capacitance value. Different amounts of sebum secretion will result in different amplitudes and trends in capacitance value changes. The calculated change in capacitance value is then converted into quantifiable second sebum secretion data (e.g., sebum secretion amount, sebum secretion level) using a preset algorithm model, thus quantifying the degree of oil production under capacitive sensing.

[0124] In this embodiment, the capacitive sensor of the vanity mirror is continuously in contact with the target area for a preset time, and the continuous capacitance values ​​within the preset time are collected. Then, the second oil secretion data of the target area is derived based on the change in capacitance value within the preset time. This method abandons the instantaneous capacitance value detection method of single contact, effectively avoiding detection errors caused by factors such as inaccurate instantaneous contact and interference from temporary water stains and sweat on the skin surface. By utilizing the correlation between the change in capacitance value and the state of oil, the results of capacitive sensing detection are more consistent with the actual oil production state of the target area, greatly improving the detection accuracy and reliability of the second oil secretion data. At the same time, the continuous contact detection method is simple to operate and adapts to the daily use of vanity mirrors. It does not require the subject to perform complex operations, ensuring both detection accuracy and ease of use. It provides high-quality capacitive sensing oil secretion data support for subsequent fusion of multi-dimensional data to determine the cleanliness state.

[0125] In one embodiment, such as Figure 4 As shown, a method for detecting and indicating the state of an object is provided. Taking the application of this method to a dressing mirror as an example, it also includes the following steps:

[0126] Step S401: Perform oil feature extraction processing on the part image to obtain the oil features of the target part; the part image is obtained by acquiring the target part under the target wavelength provided by the dressing mirror; the target part includes at least the face and head of the subject to be detected.

[0127] Step S402: Perform light reflection analysis on the part image to obtain the reflection features of the target part; the reflection features are used to characterize the optical signals reflected by the target part.

[0128] Step S403: Based on the characteristics of oil and reflectivity, obtain the first oil secretion data of the target area.

[0129] Step S404: While the capacitive sensor of the vanity mirror is in continuous contact with the target area for a preset time, the capacitance value of the target area within the preset time is obtained through the capacitive sensor; based on the change in capacitance value within the preset time, the second oil secretion data of the target area is obtained.

[0130] Step S405: Based on the first sebum secretion data and the second sebum secretion data, determine the cleanliness status of the target area of ​​the object to be tested.

[0131] Step S406: Input the historical sebum secretion data of the target area in the historical time period into the sebum secretion prediction model corresponding to the object to be detected, and obtain the predicted sebum secretion data of the target area in the current time period.

[0132] Step S407: Based on the difference between the target sebum secretion data and the predicted sebum secretion data, generate sebum change prompt information for the target area.

[0133] Step S408: Based on the basic prompt information and oil change prompt information corresponding to the target oil secretion data, generate prompt information for the target area.

[0134] Step S409: Obtain the lighting data of the environment where the vanity mirror is located; determine the target lighting parameters of the vanity mirror's lighting module based on the lighting data and prompt information; control the vanity mirror to adjust the current lighting parameters of the lighting module to the target lighting parameters.

[0135] The above-mentioned method for detecting and prompting the state of an object can achieve the following beneficial effects: By using a vanity mirror to integrate image acquisition and capacitive sensing for dual detection, first and second sebum secretion data are obtained for the target areas of the object to be detected, including the face and head. Through the fusion analysis of multi-dimensional data, the cleanliness status of the target areas is accurately determined, and prompt information is generated and displayed on the vanity mirror based on this cleanliness status. This not only achieves multi-dimensional and accurate quantitative monitoring of facial and scalp oil production, effectively improving the accuracy and reliability of cleanliness status judgment, but also provides personalized prompts that meet the actual cleanliness needs of the object to be detected. This allows the object to intuitively and promptly grasp the cleanliness status of its face and scalp, helping it to make scientific cleanliness and care decisions. The entire detection and prompting process can be completed using a vanity mirror without the need for additional professional detection instruments, greatly improving the convenience of detecting the cleanliness status of the object to be detected. It can also be conveniently used as a vanity mirror in a car.

[0136] To more clearly illustrate the object state detection and prompting method provided in this disclosure, the following example specifically describes the application scenario of the above-mentioned object state detection and prompting method. For instance... Figure 5 As shown, a method for detecting and indicating the state of an object is provided, which can be applied to a dressing mirror, and specifically includes the following:

[0137] 1. Start-up (start-up phase): When the object to be detected approaches the dressing mirror, the intelligent recognition module detects the object through infrared sensing or image capture and automatically starts the system; or the object to be detected can be manually started through the control module.

[0138] 2. Data acquisition stage: The camera of the intelligent recognition module captures images of the face and hair of the object to be detected, and the sensor simultaneously collects data such as facial oil, and transmits the collected images and data to the data processing module.

[0139] 3. Data Analysis Stage: The data processing module uses image recognition algorithms to analyze the cleanliness of the hair (such as whether there is obvious oil or dandruff accumulation), and calculates the facial oil content using an oil content analysis algorithm, comparing it with the preset cleanliness standard threshold.

[0140] 4. Generation phase prompts:

[0141] (1) If the facial oil content exceeds the threshold, a prompt message such as "Your face is oily, it is recommended to use a gentle cleansing tool to clean your face" will be generated.

[0142] (2) If the hair cleanliness is detected to be below the threshold, a prompt message such as "Hair is slightly oily, it is recommended to wash it to keep it clean and fresh" will be generated;

[0143] If the subject's face and hair are in good condition or are cleaned before a second test, and the subject passes the test, an optimized message such as "You're in good condition today, please enjoy your day" will be generated.

[0144] 5. Information Display and Lighting Adjustment Stage: The data processing module sends the generated prompts to the display module, which then displays the prompts in a specific area of ​​the mirror. Simultaneously, the control module adjusts the brightness and color temperature of the lighting module based on the ambient light data and the prompts from the data processing module, providing a comfortable environment for observation and cleaning of the object to be inspected.

[0145] In this embodiment, the following beneficial effects can be achieved: (1) It can objectively and accurately monitor the cleanliness of the subject's face, such as oil production and hair cleanliness, solving the problem of existing dressing mirrors relying on subjective judgment by the naked eye and improving the scientific nature of the cleanliness judgment; (2) With the help of the display module, it provides targeted prompts based on the monitoring results, enabling the subject to understand its own cleanliness needs in a timely manner, avoiding the problems of over-cleaning or untimely cleaning, which is conducive to maintaining skin and hair health; (3) It integrates the light adjustment function and links with the intelligent monitoring, which can provide a suitable light environment for the subject to be tested, making it easier for the subject to observe the cleanliness effect more clearly and further improving the ease of use; (4) By adding the storage module, it forms a care file for the subject to be tested and provides personalized suggestions, making the product more in line with the individual needs of the subject to be tested, improving the practicality and competitiveness of the product.

[0146] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0147] Based on the same inventive concept, this application also provides an object state detection and prompting device for implementing the object state detection and prompting method described above. The solution provided by this device is similar to the implementation scheme described in the above method. Therefore, the specific limitations of one or more object state detection and prompting device embodiments provided below can be found in the limitations of the object state detection and prompting method described above, and will not be repeated here.

[0148] In one embodiment, such as Figure 6 As shown, an object status detection and prompting device 600 is provided, including: a first grease detection module 601, a second grease detection module 602, a cleanliness status determination module 603, and a prompt information display module 604, wherein:

[0149] The first oil detection module 601 is used to obtain first oil secretion data of the target area based on the area image of the target area of ​​the subject to be detected obtained through the dressing mirror; the target area includes at least the face and head of the subject to be detected.

[0150] The second oil detection module 602 is used to obtain the second oil secretion data of the target area based on the capacitance value of the target area obtained through the dressing mirror.

[0151] The cleaning status determination module 603 is used to determine the cleaning status of the target part of the object to be tested based on the first oil secretion data and the second oil secretion data.

[0152] The prompt information display module 604 is used to generate prompt information for the object to be detected based on the cleaning status and display the prompt information on the vanity mirror.

[0153] In one embodiment, the prompt information display module 604 is further configured to input historical sebum secretion data of the target area in a historical time period into the sebum secretion prediction model corresponding to the object to be detected, to obtain the predicted sebum secretion data of the target area in the current time period; generate sebum change prompt information of the target area based on the difference between the target sebum secretion data and the predicted sebum secretion data; and generate prompt information for the target area based on the basic prompt information and sebum change prompt information corresponding to the target sebum secretion data.

[0154] In one embodiment, the object status detection and prompting device 600 further includes a lighting parameter adjustment module, used to acquire the illumination data of the environment where the dressing mirror is located; determine the target illumination parameters of the dressing mirror's lighting module based on the illumination data and prompting information; and control the dressing mirror to adjust the current illumination parameters of the lighting module to the target illumination parameters.

[0155] In one embodiment, the first oil detection module 601 is further configured to perform oil feature extraction processing on the part image to obtain the oil features of the target part; the part image is acquired by collecting the target part at the target wavelength provided by the dressing mirror; the part image is subjected to light reflection analysis processing to obtain the reflective features of the target part; the reflective features are used to characterize the optical signal reflected by the target part; and the first oil secretion data of the target part is obtained based on the oil features and the reflective features.

[0156] In one embodiment, the second oil detection module 602 is further configured to, when the capacitive sensor of the dressing mirror is in continuous contact with the target area for a preset time, obtain the capacitance value of the target area within the preset time through the capacitive sensor; and obtain the second oil secretion data of the target area based on the change in capacitance value within the preset time.

[0157] In one embodiment, the cleaning status determination module 603 is further configured to obtain target oil secretion data of the target area based on the temperature and humidity data of the environment where the object to be tested is located, the first oil secretion data, and the second oil secretion data; if the target oil secretion data exceeds a preset oil secretion threshold, the cleaning status of the target area of ​​the object to be tested is confirmed to be substandard; if the target oil secretion data does not exceed the oil secretion threshold, the cleaning status of the target area of ​​the object to be tested is confirmed to be compliant.

[0158] In one embodiment, the object status detection and prompting device 600 further includes an oil data correction module, which is used to fuse the first oil secretion data and the second oil secretion data to obtain candidate oil secretion data of the target area; and to correct the candidate oil secretion data according to the temperature and humidity data of the environment where the object to be detected is located to obtain the target oil secretion data of the target area.

[0159] Each module in the aforementioned object status detection and prompting device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor within the vanity mirror in hardware form or stored in the memory of the vanity mirror in software form, so that the processor can call and execute the corresponding operations of each module.

[0160] In one exemplary embodiment, a dressing mirror is provided, the internal structure of which can be shown in the diagram below. Figure 7 As shown, the vanity mirror includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for detecting and prompting about the state of an object. The display unit of the vanity mirror forms a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the vanity mirror can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the outer shell of the vanity mirror, or an external keyboard, touchpad, or mouse, etc.

[0161] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the dressing mirror to which the present application is applied. A specific dressing mirror may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0162] In one embodiment, a dressing mirror is also provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps in the above method embodiments.

[0163] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0164] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0165] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0166] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0167] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0168] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for detecting and indicating the state of an object, characterized in that, The method includes: Based on the image of the target area of ​​the subject obtained through a vanity mirror, the first sebum secretion data of the target area is obtained; the target area includes at least the face and / or head of the subject. Based on the capacitance value of the target area obtained through the dressing mirror, the second sebum secretion data of the target area is obtained; Based on the first oil secretion data and the second oil secretion data, the cleanliness status of the target area of ​​the object to be tested is determined; Based on the cleanliness status, a prompt message is generated for the object to be detected, and the prompt message is displayed on the vanity mirror.

2. The method according to claim 1, characterized in that, The step of determining the cleanliness status of the target area of ​​the object to be tested based on the first sebum secretion data and the second sebum secretion data includes: Based on the temperature and humidity data of the environment in which the object to be tested is located, the first oil secretion data, and the second oil secretion data, the target oil secretion data of the target location is obtained. If the target sebum secretion data exceeds the preset sebum secretion threshold, then the cleanliness of the target part of the object to be tested is confirmed to be substandard. If the target sebum secretion data does not exceed the sebum secretion threshold, then the cleanliness of the target area of ​​the object to be tested is confirmed to be up to standard.

3. The method according to claim 2, characterized in that, The step of obtaining target sebum secretion data for the target location based on the temperature and humidity data of the environment where the object to be tested is located, the first sebum secretion data, and the second sebum secretion data includes: The first and second sebum secretion data are fused to obtain candidate sebum secretion data for the target site. Based on the temperature and humidity data of the environment in which the object to be tested is located, the candidate oil secretion data is corrected to obtain the target oil secretion data of the target location.

4. The method according to claim 2, characterized in that, The step of generating a prompt message for the object to be detected based on the cleanliness status includes: The historical sebum secretion data of the target area in a historical time period is input into the sebum secretion prediction model corresponding to the object to be detected, so as to obtain the predicted sebum secretion data of the target area in the current time period. Based on the difference between the target sebum secretion data and the predicted sebum secretion data, a sebum change alert is generated for the target area. Based on the basic prompt information corresponding to the target sebum secretion data and the sebum change prompt information, prompt information is generated for the target area.

5. The method according to claim 1, characterized in that, After displaying the prompt message on the vanity mirror, the system also includes: Obtain the lighting data of the environment in which the dressing mirror is located; Based on the illumination data and the prompt information, determine the target illumination parameters of the dressing mirror's lighting module; The dressing mirror is controlled to adjust the current lighting parameters of the lighting module to the target lighting parameters.

6. The method according to claim 1, characterized in that, The step of obtaining the first sebum secretion data of the target area based on the area image of the target area of ​​the object to be detected obtained through a vanity mirror includes: The image of the area is processed to extract oil features, thereby obtaining the oil features of the target area; the image of the area is obtained by capturing the target area at the target wavelength provided by the dressing mirror. The image of the area is subjected to light reflection analysis to obtain the reflective features of the target area; the reflective features are used to characterize the optical signals reflected by the target area. Based on the oil characteristics and the reflective characteristics, the first oil secretion data of the target area is obtained.

7. The method according to claim 1, characterized in that, The step of obtaining second sebum secretion data for the target area based on the capacitance value of the target area obtained through the vanity mirror includes: When the capacitive sensor of the vanity mirror is in continuous contact with the target area for a preset time, the capacitance value of the target area within the preset time is obtained through the capacitive sensor. Based on the change in capacitance value within the preset time period, the second sebum secretion data of the target area is obtained.

8. A device for detecting and indicating the state of an object, characterized in that, The device includes: The first oil detection module is used to obtain first oil secretion data of the target area based on the area image of the target area of ​​the object to be detected obtained through a dressing mirror; the target area includes at least the face and head of the object to be detected. The second oil detection module is used to obtain the second oil secretion data of the target area based on the capacitance value of the target area obtained through the dressing mirror; A cleanliness status determination module is used to determine the cleanliness status of the target area of ​​the object to be tested based on the first oil secretion data and the second oil secretion data. The prompt information display module is used to generate prompt information for the object to be tested based on the cleaning status, and display the prompt information on the dressing mirror.

9. A dressing mirror, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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