Intelligent dressing mirror system based on non-inductive interaction and clothing recording method

Abstract

The invention relates to the technical field of smart home and visual identification, in particular to an intelligent dressing mirror system based on non-inductive interaction and a clothes collecting method, and the intelligent dressing mirror system comprises a dressing mirror body which is used for displaying a whole-body mirror image picture of a user; the intelligent acquisition communication module is mounted on the dressing mirror body and is used for sensing a human body and acquiring an original image including a whole-body image of a user; and the cloud server communicates with the intelligent acquisition communication module and is used for analyzing and processing the acquired whole body image of the user and pushing a result to a mobile terminal of the user. Through the system architecture of hardware collection, cloud computing and mobile phone terminal interaction, the problems that an existing intelligent mirror is high in cost and poor in privacy, and traditional APP clothes input is tedious are solved.

Description

Technical Field

[0001] This invention relates to the fields of smart home and visual recognition technology, specifically to a smart dressing mirror system and clothing collection method based on seamless interaction. Background Technology

[0002] With the development of smart home technology, smart dressing mirrors, as a new type of smart home product, are gradually attracting people's attention. Currently, smart dressing mirrors on the market are mainly divided into two categories: one is a smart mirror with a display screen, and the other is a wardrobe management app that only supports mobile phones.

[0003] Smart mirrors with integrated displays typically embed a large LCD / OLED screen beneath the mirror surface and are equipped with a camera. These mirrors can display outfit suggestions, weather information, and other content, but they have the following drawbacks: 1. Privacy concerns: Cameras are exposed in the bedroom environment for a long time, which makes users feel insecure and lacks a clear physical blocking mechanism.

[0004] 2. High cost: Large-size displays result in extremely high BOM (Bill of Materials) costs.

[0005] 3. Poor aesthetics: When the screen is off, a noticeable black display area appears on the mirror, which ruins the overall aesthetic appeal of the mirror as furniture.

[0006] 4. Light pollution: The light emitted by the screen will interfere with the indoor ambient light and generate a lot of heat.

[0007] Pure mobile wardrobe management apps require users to upload photos of clothing via their phones and manually edit the information. This method has the following drawbacks: 1. Cumbersome data entry: Users need to actively lay each piece of clothing flat, take photos, cut, and label it. The high barrier to entry makes it easy for users to churn in the early stages (cold start phase), making it impossible to build an effective wardrobe database.

[0008] In summary, existing technologies lack a solution that can integrate into the home environment in a low-cost and highly private manner, while also solving the problem of clothing collection and recommendation automatically and with low resistance. Summary of the Invention

[0009] To address the aforementioned issues, a smart dressing mirror system and clothing data entry method based on seamless interaction are provided. Through a system architecture of "hardware data acquisition + cloud computing + mobile terminal interaction," the system solves the problems of high cost, poor privacy, and cumbersome clothing data entry in traditional apps found in existing smart mirrors.

[0010] To address the problems of existing technologies, this invention provides an intelligent dressing mirror system based on contactless interaction, comprising: The full-length mirror itself is used to display a full-body image of the user; An intelligent data acquisition and communication module is installed on the dressing mirror body to sense the human body and acquire raw images containing the user's full-body image; The cloud server communicates with the intelligent acquisition and communication module to analyze and process the acquired full-body images of the user and push the results to the user's mobile terminal.

[0011] As a specific embodiment of the present invention, the intelligent acquisition and communication module includes: A camera unit is mounted on the dressing mirror body to capture the original image; The processor unit has a built-in communication module for uploading the captured full-body images to a cloud server and the user's mobile terminal.

[0012] As a specific embodiment of the present invention, the intelligent acquisition and communication module further includes: The sensing unit is used to sense the human body and enable automatic wake-up. An environmental interaction unit is used to provide light or audio feedback; The environment interaction unit includes: Intelligent lighting subunit, used for supplemental lighting and status indication; The audio subunit is used for photo prompts and announcements.

[0013] In one specific embodiment of the present invention, the intelligent data acquisition and communication module is disposed on the front or back side of the dressing mirror body. When the intelligent acquisition and communication module is located on the back side of the dressing mirror body, an image acquisition window is opened on the mirror surface of the dressing mirror body, or the area of ​​the dressing mirror body facing the intelligent acquisition and communication module is a light-transmitting area.

[0014] As a specific embodiment of the present invention, the image acquisition window is provided with a movable sliding cover for obscuring the lens of the camera unit.

[0015] As a specific embodiment of the present invention, the sliding cover has a secondary mirror on the side facing the user. When the lens of the camera unit is blocked, the secondary mirror completely covers the image acquisition window.

[0016] A method for clothing collection based on non-contact interaction, which uses a smart dressing mirror system based on non-contact interaction for image acquisition, analysis and processing, includes the following steps: Step S1, System wake-up and preparation, The system detects the user's approach through the sensing unit, wakes them up, and initializes. Step S2, Image Acquisition and Preliminary Processing The system acquires the original image through the camera unit and provides preliminary status feedback; Step S3, AI recognition and data processing, The system uses the processor unit to perform AI analysis on the acquired full-body images and extract wearable features; Step S4: Data entry and feedback. The system will archive the analysis and identification results and provide feedback to the user.

[0017] In a specific embodiment of the present invention, in step S1, when a user's preset distance range is detected and the dwell time exceeds a preset threshold, a wake-up signal is triggered; after receiving the wake-up signal, the processor unit controls the camera unit to switch from low-power mode to working mode, and at the same time controls the environmental interaction unit to provide supplementary lighting.

[0018] In one specific embodiment of the present invention, in step S2, the camera unit captures a full-body image of the user at the current moment and provides a sound and light synchronized shooting status indication through the environmental interaction unit.

[0019] In a specific embodiment of the present invention, in step S3, the processor unit uploads the full-body image data to the cloud server for image processing, identifies all wearing features in the image through an image recognition algorithm, analyzes the attribute information of each wearing feature, and finally combines the external data obtained by the system to evaluate the rationality of the outfit.

[0020] As a specific embodiment of the present invention, in step S4, the system compares each currently identified wearable feature with the user's personal wardrobe database stored in the system to determine whether it is a new wearable feature. If it is a new wearable feature, it will be automatically archived into the database, and a feature profile will be created. If it is an old wearing feature, then update the wearing frequency record for that wearing feature; After the comparison is completed, the comparison completion status is indicated by sound and light synchronization through the environmental interaction unit, and the results of the outfit rationality assessment and the personal clothing database update results are pushed to the user's mobile terminal simultaneously.

[0021] The advantages of this invention compared to the prior art are: 1. Enhanced privacy protection: Through a physical sliding structure or hidden design, visual data collection is physically cut off, completely eliminating users' concerns about privacy leaks.

[0022] 2. Reduced cost and energy consumption: The use of a purely physical reflective mirror to replace the expensive display screen significantly reduces hardware costs and standby power consumption.

[0023] 3. Improved clothing entry efficiency: Through seamless entry and lightning-fast cold start functions, clothing can be automatically entered without the user's awareness, solving the problem of cumbersome entry in traditional apps.

[0024] 4. Enhanced integration with home décor: The screenless design makes the product a regular high-end mirror when not in use, with excellent aesthetics, allowing it to seamlessly blend into the home environment.

[0025] 5. Personalized service provision: Through artificial intelligence algorithms, we provide personalized services for users by recommending outfits and managing their wardrobes. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of a first embodiment of the present invention, in which the intelligent data acquisition and communication module of the intelligent dressing mirror system based on contactless interaction is installed on the back side of the dressing mirror body.

[0027] Figure 2 This is a schematic diagram of a second embodiment of the present invention, in which the intelligent data acquisition and communication module of the intelligent dressing mirror system based on contactless interaction is located on the back side of the dressing mirror body.

[0028] Figure 3 This is a system interaction flowchart of a clothing collection method based on seamless interaction according to the present invention.

[0029] The following are the labels in the diagram: 1. Dressing mirror body; 2. Intelligent acquisition and communication module; 3. Camera unit; 4. Sliding cover; 5. Image acquisition window; 6. Light-transmitting area; 7. Mobile terminal. Detailed Implementation

[0030] To further understand the features, technical means, and specific objectives and functions achieved by the present invention, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

[0031] Reference Figure 1 and Figure 2 As shown, a smart dressing mirror system based on seamless interaction includes a dressing mirror body 1, a smart acquisition and communication module 2, and a cloud server. The dressing mirror body 1 is used to display a full-body mirror image of the user. The smart acquisition and communication module 2 is installed on the dressing mirror body 1 and is used to sense the human body and acquire raw images containing the user's full-body image. The cloud server communicates with the smart acquisition and communication module 2 to analyze and process the acquired full-body image of the user and push the results to the user's mobile terminal 7.

[0032] As a specific embodiment of the present invention, the intelligent acquisition and communication module 2 includes a camera unit 3 and a processor unit; the camera unit 3 is installed on the dressing mirror body 1 to acquire the original image; the processor unit has a built-in communication module for uploading the acquired full-body image to a cloud server and the user's mobile terminal 7.

[0033] As a specific embodiment of the present invention, the intelligent acquisition and communication module 2 further includes a sensing unit and an environmental interaction unit; the sensing unit is used to sense the human body and realize automatic wake-up; the environmental interaction unit is used to provide light or audio feedback; wherein, the environmental interaction unit includes an intelligent lighting subunit and an intelligent lighting subunit, the intelligent lighting subunit being used for supplementary lighting and status prompts; the audio subunit being used for photo prompts and prompt voice broadcasts.

[0034] In one specific embodiment of the present invention, the intelligent acquisition and communication module 2 is disposed on the front or back side of the dressing mirror body 1. When the intelligent acquisition and communication module 2 is disposed on the back side of the dressing mirror body 1, an image acquisition window 5 is provided on the mirror surface of the dressing mirror body 1, or the area of ​​the dressing mirror body 1 facing the intelligent acquisition and communication module 2 is a light-transmitting area 6 (e.g., Figure 2 (As shown).

[0035] As a specific embodiment of the present invention, refer to Figure 1 As shown, the image acquisition window 5 is provided with a movable sliding cover 4 for blocking the lens of the camera unit 3.

[0036] As a specific embodiment of the present invention, the sliding cover 4 is provided with a secondary mirror on the side facing the user. When the lens of the camera unit 3 is blocked, the secondary mirror completely covers the image acquisition window 5.

[0037] A method for clothing collection based on non-contact interaction, which uses a smart dressing mirror system based on non-contact interaction for image acquisition, analysis and processing, includes the following steps: Step S1, System wake-up and preparation: The system detects the user's approach through the sensing unit, wakes up the user, and initializes the system.

[0038] Step S2, Image Acquisition and Preliminary Processing: The system acquires a raw image containing the user's full-body image through the camera unit 3 and provides preliminary status feedback.

[0039] Step S3, AI recognition and data processing: The system uses the processor unit to perform AI analysis on the acquired full-body images and extract wearable features.

[0040] Step S4: Data entry and feedback. The system will archive the analysis and identification results and provide feedback to the user.

[0041] In a specific embodiment of the present invention, in step S1, when a user's preset distance range is detected and the dwell time exceeds a preset threshold, a wake-up signal is triggered; after receiving the wake-up signal, the processor unit controls the camera unit 3 to switch from low-power mode to working mode, and at the same time controls the environmental interaction unit to provide supplementary lighting.

[0042] In a specific embodiment of the present invention, in step S2, the camera unit 3 captures a full-body image of the user at the current moment and provides a sound and light synchronized shooting status indication through the environmental interaction unit.

[0043] In a specific embodiment of the present invention, in step S3, the processor unit uploads the full-body image data to the cloud server for image processing, identifies all wearing features in the image through an image recognition algorithm, analyzes the attribute information of each wearing feature, and finally combines the external data obtained by the system to evaluate the rationality of the outfit.

[0044] In a specific embodiment of the present invention, in step S4, the system compares each currently identified wearing feature with the user's personal wardrobe database stored in the system to determine whether it is a new wearing feature; if it is a new wearing feature, it is automatically archived into the database to create a feature file; if it is an old wearing feature, the wearing frequency record of that wearing feature is updated; after the comparison is completed, the comparison completion status is indicated by sound and light synchronization through the environmental interaction unit, and the results of the outfit rationality assessment and the update results of the personal clothing database are pushed to the user's mobile terminal 7 simultaneously.

[0045] Reference Figure 3 The diagram shows a system interaction flowchart of a clothing collection method based on seamless interaction according to the present invention. The specific process is described as follows: The sensing unit detects the distance relative to the intelligent acquisition and communication module 2 in real time. When it detects that a user has entered a preset distance range (e.g., 0.5 meters to 1.5 meters) and stayed for more than a preset threshold (e.g., 3 seconds), it triggers a wake-up signal. After receiving the wake-up signal, the processor unit switches the camera unit 3 from low-power mode to working mode, and at the same time controls the environmental interaction unit to provide supplementary lighting. Specifically, the intelligent light subunit illuminates a warm white soft light to provide uniform illumination for subsequent image acquisition.

[0046] Then, camera unit 3 is activated to capture a full-body image of the user, thus fully recording the user's "outfit for the day." At the same time, the shooting status is prompted by sound and light synchronization through the environmental interaction unit, specifically by illuminating a breathing light (such as a blue breathing light) through the intelligent lighting subunit and emitting a shutter sound through the audio subunit.

[0047] The processor unit uploads the acquired images to a cloud server for processing, where they are analyzed using image recognition algorithms. Specifically, image segmentation algorithms are used to automatically extract the background and separate the user subject. Computer vision algorithms are then used to identify individual items (such as tops, bottoms, and shoes) within the image and analyze their attribute information, including color, material, and style. Finally, external data acquired by the system (such as local weather information) is combined to evaluate the appropriateness of the current outfit.

[0048] Finally, the identified clothing information is compared with the user's personal wardrobe database to determine if it is new. If it is new, it is automatically archived and a clothing profile is created; if it is old, the wearing frequency record for that clothing is updated. After recognition, the environmental interaction unit provides synchronized audio and visual prompts (e.g., a breathing light flashes green once, and a buzzer sounds a "click," providing the user with immediate visual and auditory feedback). The user's mobile app simultaneously receives a push notification informing them that "Today's outfit has been recorded" and displaying detailed clothing information. If the system determines that the current outfit has a scene conflict (e.g., the clothing material is not suitable for today's weather), the environmental interaction unit provides synchronized audio and visual prompts (e.g., a breathing light flashes yellow as a warning and a specific prompt sound), and the mobile app simultaneously pops up a window providing specific outfit suggestions (e.g., providing several outfit suggestions based on weather, location, schedule, etc., solving the dilemma of what to wear today).

[0049] It should be noted that a quick centralized clothing entry mode is also available for new users. This is the lightning-fast cold start entry mode.

[0050] Specifically, the user initiates the continuous recording mode command to the intelligent acquisition and communication module 2 via mobile terminal 7. The intelligent acquisition and communication module 2 continuously monitors the acquisition area within a preset time period. When it detects a single garment held by the user in the acquisition area, it automatically triggers continuous image capture. The system only extracts features and creates files for the identified garment, skipping the full-body image analysis step. After each garment is recorded, the system triggers a short audio or light effect feedback to indicate completion, allowing the user to immediately proceed with the recording of the next garment.

[0051] It should also be noted that this invention provides dual privacy protection at both the physical and technical levels. That is, it has a privacy protection mechanism.

[0052] Specifically, when the user closes the slider 4 to block the camera, the optical path is physically cut off. Data captured on the local device is then uploaded to the cloud without human intervention, ensuring the security of user privacy data during transmission and processing.

[0053] The above embodiments only illustrate one or more implementations of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the appended claims.

Claims

1. A smart dressing mirror system based on contactless interaction, characterized in that, include: The full-length mirror itself is used to display a full-body image of the user; An intelligent data acquisition and communication module is installed on the dressing mirror body to sense the human body and acquire raw images containing the user's full-body image; The cloud server communicates with the intelligent acquisition and communication module to analyze and process the acquired full-body images of the user and push the results to the user's mobile terminal.

2. The intelligent dressing mirror system based on contactless interaction according to claim 1, characterized in that, The intelligent data acquisition and communication module includes: A camera unit is mounted on the dressing mirror body to capture the original image; The processor unit has a built-in communication module for uploading the captured full-body images to the cloud server and the user's mobile terminal. The intelligent data acquisition and communication module also includes: The sensing unit is used to sense the human body and enable automatic wake-up. An environmental interaction unit is used to provide light or audio feedback; The environment interaction unit includes: Intelligent lighting subunit, used for supplemental lighting and status indication; The audio subunit is used for photo prompts and announcements.

3. The intelligent dressing mirror system based on contactless interaction according to claim 2, characterized in that, The image acquisition window is equipped with a movable sliding cover for obscuring the lens of the camera unit.

4. A method for clothing collection based on seamless interaction, characterized in that, Image acquisition, analysis, and processing using the smart dressing mirror system based on contactless interaction as described in any one of claims 1-3 includes the following steps: Step S1, System wake-up and preparation, The system detects the user's approach through the sensing unit, wakes them up, and initializes. Step S2, Image Acquisition and Preliminary Processing The system acquires the original image through the camera unit and provides preliminary status feedback; Step S3, AI recognition and data processing, The system uses the processor unit to preprocess the acquired full-body images and uploads the preprocessed data to the cloud server for analysis and recognition. Step S4: Data entry and feedback. The system will archive the analysis and identification results and provide feedback to the user.

5. The method for clothing collection based on seamless interaction according to claim 4, characterized in that, In step S1, when a user's preset distance range is detected and the dwell time exceeds a preset threshold, a wake-up signal is triggered. After receiving the wake-up signal, the processor unit controls the camera unit to switch from low-power mode to working mode, and at the same time controls the environmental interaction unit to provide supplementary lighting.

6. The method for clothing collection based on seamless interaction according to claim 5, characterized in that, In step S2, the camera unit captures an original image that meets the requirements at the current moment, and provides a sound and light synchronized shooting status indication through the environmental interaction unit.

7. The method for clothing collection based on seamless interaction according to claim 6, characterized in that, In step S3, the cloud server identifies all wearing features in the image using an image recognition algorithm and analyzes the attribute information of each wearing feature. Finally, it combines the external data obtained by the system to evaluate the rationality of the outfit. In step S4, the system compares each currently identified wearable feature with the user's personal wardrobe database stored in the system to determine whether it is a new wearable feature. If it is a new wearable feature, it will be automatically archived into the database, and a feature profile will be created. If it is an old wearing feature, then update the wearing frequency record for that wearing feature; After the comparison is completed, the comparison completion status is indicated by sound and light synchronization through the environmental interaction unit, and the results of the outfit rationality assessment and the personal clothing database update results are pushed to the user's mobile terminal simultaneously.

8. The method for clothing collection based on seamless interaction according to claim 7, characterized in that, When the system recognizes that the full-body image is the user holding and displaying each item of clothing in front of the mirror, it enters the centralized data entry mode and does not perform an assessment of the appropriateness of the outfit. In the centralized data entry mode, the system analyzes and automatically archives the wearable items displayed by the user in the image one by one as new wearable features. This includes a smart dressing mirror system based on seamless interaction.

9. The method for clothing collection based on seamless interaction according to claim 8, characterized in that, The processor unit has a built-in edge computing subunit for performing the pre-processing, which includes the following steps: Step S3.1, Real-time key point detection, A lightweight human keypoint detection algorithm is run on the original image to locate the user's face region, skin regions not covered by clothing, and environmentally sensitive background regions in the image in real time. Step S3.2, intra-terminal structured segmentation, Based on the key points located in step S3.1, the original image is segmented into "core attribute region" and "privacy sensitive region"; Step S3.3, edge-side desensitization treatment, Processing is performed on the aforementioned "privacy-sensitive area" to ensure that biometric data cannot be traced back; The edge-side desensitization process is completed in memory, and the original data before desensitization is immediately destroyed after being processed in memory; Step S3.4, background semantic substitution, The background area outside the clothing boundary is uniformly filled with a solid color or extracted through semantic segmentation, retaining only the silhouettes of the human body and clothing; Step S3.5, send the de-identified data out. Only the desensitized "non-sensitive structured images" and "feature vector data" are uploaded to the cloud server through an encrypted channel.

10. The method for clothing collection based on seamless interaction according to claim 9, characterized in that, The specific steps to trigger the wake-up signal are as follows: Step S1.1, Level 1 Sensing (Low Power Detection). The sensor unit monitors the displacement of objects within a preset distance range in front of the mirror in real time. When the object is detected to remain in the mirror for more than the first preset threshold, the second-level sensing is triggered. Step S1.2, Secondary perception (posture mode judgment). The camera unit captures the human body outline and key points and determines the current user's posture modality. Step S1.3, wake-up determination, When the current attitude mode meets the preset conditions, the system officially enters the working mode.

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