AR/VR for Cosmetic Visualization

Virtual makeup try-on method and device that enables users to try on multiple makeup products and elements simultaneously to provide a more intuitive and efficient virtual makeup experience. It involves generating makeup trial renderings in batches for multiple makeup trial elements and objects, rather than individually. This allows comparing multiple elements on the same face, and multiple faces with the same element. This improves efficiency and enables side-by-side comparisons of makeup trials.

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Virtual fitting and makeup system that allows users to try on clothes and makeup together in a more efficient and realistic way compared to separate virtual fitting and virtual makeup mirrors. The system generates a human body model based on user's physical characteristics, combines it with their current clothing to create a body image, and then recommends makeup based on that body image. The recommended makeup is then combined with the body image to show a recommended overall look. This allows users to see how the makeup will look with the clothes before applying it.

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Method for assisting users in applying makeup using augmented reality (AR) devices. The method involves analyzing the user's facial image to identify features like skin tone, facial shape, and contours. This facial information is then matched with auxiliary makeup solutions to create a personalized makeup plan for the user. The AR device displays a preview of the suggested makeup to the user, who can adjust it as desired. This allows the user to have a customized makeup experience tailored to their unique facial features.

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Virtual makeup try-on system that improves efficiency by accurately locating and displaying the position of the selected physical makeup to match the virtual makeup being tried. The system uses smart mirrors and trays to associate virtual and physical makeup, and during virtual trials, the system shows the tray location of the corresponding physical makeup. This allows users to quickly find and locate the exact spot to try the physical product, avoiding searching multiple trays.

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Digital makeup artist system that provides interactive makeup suggestions and tutorials to users in a way that mimics a personal makeup artist experience. The system analyzes user facial images using machine learning to identify features, skin tone, etc. Then it interacts with the user to understand their needs and preferences. Based on that, it generates customized makeup looks and tutorials synced to the user's facial image. Users can control playback, adjust steps, etc. The system also learns from user feedback to improve recommendations.

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A system for helping users see how makeup looks on them by applying makeup from other people's images. The system generates makeup information for a user's face based on makeup seen on other contributors. It applies this generated makeup to the user's own face image. The system also provides content with the applied makeup and product details to the user. This allows users to see how makeup from others looks on themselves before buying.

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Virtual makeup method that accurately recreates a user's simulated makeup application on a virtual human. The method involves capturing the user's makeup motions in real-time, selecting the correct tools and accessories based on those motions, and generating and rendering the virtual makeup accordingly. This allows more realistic virtual makeup that accurately reflects the user's intended application.

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Interactive virtual makeup system for virtual digital humans that allows users to apply makeup in real-time. It provides a makeup interface with tools to dress up the virtual digital human. When a user selects a makeup tool, it displays a floating layer with auxiliary makeup options specific to that tool. The user can then choose options to customize the makeup. This allows users to try on different makeup looks and experiment with various tools and accessories. The system uses computer vision to accurately place the makeup tools on the virtual face.

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Virtual makeup device and method that allows users to try on virtual makeup with customizable textures for a more realistic and immersive experience. The device extracts the target area like lips from a facial image, applies the desired color, and then adds specific texture components to parts of the target area for each makeup item. This enables virtual makeup with unique textures like gloss, matte, or balm for different products.

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Virtual makeup application system that allows a makeup artist to apply makeup remotely to a user's digital images in real-time. The system involves a makeup application device used by the artist and a client device used by the user. The artist requests a makeup consultation, gets images from the user, creates a 3D facial model, applies virtual makeup effects, generates commands based on artist actions, and sends them to the user's device. The user receives the commands and applies the virtual makeup to their images.

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Automatically applying digital makeup enhancements to user faces in real-time images based on previously stored makeup settings for that user. The technique involves identifying a user's face in an image, recognizing it as belonging to a registered user, and retrieving the customized digital makeup enhancements for that user. These enhancements are then applied to the user's face in the current image to generate a modified image with virtual makeup. The technique allows personalized makeup effects to be automatically applied to a user's face in real-time without manual setup.

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Simulated makeup method, system and intelligent dressing table that provides a realistic and tactile experience for simulating makeup applications. It uses a camera, display screen, makeup model and central processing unit to capture images, display them, and overlay virtual makeup. The system also has a pressure sensitive cosmetic pen for simulating the feel of applying makeup. The cosmetic pen has a sensor to detect pen pressure and transmit it to the processing unit to adjust the virtual makeup effect. This allows users to experience the sensation of applying makeup with a realistic tactile feedback.

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Artificial intelligence-based facial makeup processing method that allows users to try on virtual makeup using AI and provides personalized makeup recommendations. The method extracts facial features from a user's image, finds similar faces, applies makeup from those faces, and generates a virtual makeup image. It also recommends hairstyles based on user preferences. The AI analyzes live makeup sales videos to extract virtual makeup areas and replaces them with real products.

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Interactive makeup consulting and tutorial system using a digital makeup artist that provides personalized makeup experiences comparable to a real makeup artist. The system involves a mobile app with a database of makeup styles, products, and user preferences. A machine learning system analyzes user images to suggest styles and products. The app provides makeup tutorials with step-by-step guidance customized to the user's face.

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Method for assisting makeup using superimposed contours based on target images to provide guidance and evaluation during makeup application. The method involves obtaining makeup contours from a selected target image and overlaying them on the user's face in real time. This allows the user to see where to apply makeup based on the target image. The device also checks if the user's makeup exceeds the contours or has inconsistent colors. If so, it provides correction guidance.

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Non-contact simulation virtual makeup system that allows users to try on virtual makeup without physically applying it. It uses a camera to capture images of the user's face and analyzes them to simulate makeup application. The system has a display for showing the virtual makeup results and a processing unit that performs the makeup simulation calculations. The user faces the camera to select makeup products and see a virtual preview of how they would look. The system is designed for use in physical stores to provide a touchless, sanitary alternative to traditional makeup trials. It uses image processing instead of physical interaction like touchscreens or keyboards.

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Smart makeup mirror that provides real-time virtual makeup overlays on the user's face as they apply makeup. The mirror uses a camera, lighting, and display to capture the user's face, apply virtual makeup in real time, and overlay it on the user's reflection. This allows the user to see how the virtual makeup looks as they apply their own. The mirror also provides makeup guidance and comparison by accessing makeup databases with pre-stored schemes.

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Smart mirror that provides personalized makeup assistance using machine learning. The mirror analyzes a user's facial image to identify skin areas and detect makeup application. It compares the user's live makeup to a selected makeup plan and provides real-time feedback on areas that need adjustment. This helps the user make more efficient and consistent makeup applications by providing targeted modification suggestions.

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A digital makeup palette for augmented reality that provides personalized virtual makeup try-on experiences. It uses analysis of user's face to identify problem areas and best features, and creates custom virtual try-ons based on user-selected makeup objectives. The palette is a collection of digital makeup colors with characteristics like coverage, shade, and finish. It goes beyond physical makeup limitations by using display filters. The system analyzes user makeup steps to improve recommendations and uses machine learning to estimate problem areas and best features.

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Interactive digital makeup artist system that provides customized makeup advice and tutorials to users in a manner similar to a personal makeup artist. The system analyzes a user's face using machine learning and then guides the user through applying makeup to recreate desired looks based on factors like skin type, facial features, and preferences. It provides personalized makeup routines and tips instead of just offering predefined looks.

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Virtual makeup try-on using facial recognition and cloud storage to enable efficient, login-less makeup product recommendations and virtual application. The system allows users to quickly retrieve makeup product recommendations without logging in by matching facial images against stored sessions. The cloud server retrieves a makeup session based on the user's facial image and sends the selected products to the client device. The client then applies virtual makeup using those products on the user's facial region.

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Digital makeup palette that can be used for e-commerce personalization as well as for a personalized augmented reality experience. The palette includes characteristics such as coverage, shade, and finish.

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Augmented reality makeup try-on feature in messaging apps that lets users see how makeup looks would appear on their face using AR overlays. The feature allows users to apply virtual makeup to their own face in real-time by capturing an image or video, selecting a makeup product from a list, and seeing the product applied to their face as an overlay. The AR makeup try-on can be persistent while the video is being captured, and the selected makeup remains toggled.

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Display method for electronic devices like smartphones to provide all-round makeup assistance and guidance to users. The method involves displaying the user's face image and a simulated face with makeup side by side. Users can enlarge parts of the original face or the makeup face for detailed viewing. It allows users to compare, analyze and learn from their original face and the makeup. Other features like freezing, zooming, modifying, saving makeup, and voice commands enhance the makeup experience.

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Providing virtual makeup during video communication using facial recognition to selectively apply makeup effects to specific parts of a user's face. The system detects the user's face, extracts facial parts, applies makeup effects, and enables communication with the virtual makeup applied. It allows users to see themselves with virtual makeup during video calls by identifying, isolating, and modifying their facial features.

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Virtual makeup try-on using augmented reality (AR) to allow users to try on makeup in real-world scenes. The method involves acquiring user position information, identifying the scene, and retrieving interactive content associated with that scene from a server. AR is used to display the interactive content overlaid on the scene. Users can interact with the AR content to view videos, comments, and other updates related to the scene. The user's face is also scanned and AR makeup templates are applied to it. This provides a realistic and immersive virtual makeup experience that incorporates AR interaction with the real world.

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Virtual makeup try-on method that allows users to test makeup virtually using their own facial images. The method involves identifying the area and intensity of makeup application when a user operates on their face in a video. Then, when the user wants to try a specific type of makeup, it renders that makeup just on the identified area with the same intensity as the user's face operation. This allows customized, virtual makeup with different depths and effects based on the user's facial movements.

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A lightweight method for automatic face makeup using a mobile device that allows flexible, natural-looking makeup application with adjustable intensity. The method involves taking a face image, detecting facial features, allowing user selection of interactive makeup mode, applying makeup to the image using templates, and outputting the result. The templates are annotated with feature points for accurate replacement. The method enables customizable makeup effects and face replacement with controllable areas and filtering.

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Image processing system for realistic make-up simulation using adjustable glitter expression based on user and display area posture. The system displays captured user face in one area and cosmetic image in another. It detects the posture of the user and display areas. Then, it adjusts the glitter effect of the make-up image and/or cosmetic image based on the detected posture. This provides more accurate and realistic glitter effects that change with user and display orientation.

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Virtual makeup trying guidance method that can be used for a variety of purposes, including a trial-installation effect of lipstick, eye shadow and the like. The method includes collecting face images of a target user, combining them with images corresponding to a plurality of colors and images corresponding to the colors in a plurality of action states, comparing the selected makeup effect with the makeup effect of the second makeup trial area, and prompting the target user to modify the makeup.

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Virtual makeup try-on method that allows users to dynamically customize the applied makeup effect by moving their fingers or tools over their face. It monitors the position and number of operations when the user points at a target area and renders the makeup effect dynamically. This allows users to draw different effects with various techniques, customizing the makeup. It overcomes the issue of standardized makeup steps and lack of customization in existing virtual makeup methods.

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A method for using a skin measuring and beautifying system that enables users to try on clothes, makeup, and accessories virtually while also measuring their skin quality, complexion, and facial features. The system uses smart mirrors and servers to generate 3D body models from user photos and apply makeup and clothing virtually. It analyzes skin color, texture, and blushing to assess skin quality. It also checks facial features to create the models. This provides a more comprehensive virtual fitting and beautifying experience.

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Virtual fitting of a facial makeup that can be used for a variety of purposes, such as cartoon masks and drama facial makeup, to enhance its fitting experience for a user. The method includes acquiring a sample face image through a camera, extracting a plurality of facial feature points from the sample face image, and matching the vertex texture coordinates to the facial makeup model through the facial three-dimensional mesh model, thereby realizing real-time virtual try-on of the facial makeup.

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Interactive method for assisting makeup using a camera to provide a more realistic and personalized virtual makeup experience. The method involves capturing depth and color images, fusing the virtual makeup with the user's face using the depth data, and displaying the result. It allows trying on virtual makeup that better matches the user's features by combining the depth information with facial feature extraction.

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Customized makeup diagnosis system using augmented reality that allows users to virtually try on makeup and get expert feedback. The system receives user-captured images, synthesizes augmented reality makeup content onto the images, sends them to experts for diagnosis, and returns the comments to the users. It involves modules like user subscription, image input, augmented reality selection, composition synthesis, and comment transmission. The augmented reality makeup content includes backgrounds, costumes, and hairstyles that are placed around the user's face in the synthesized images. The brightness and saturation of the AR content is adjusted to match the user's skin tone. This allows users to test how makeup will look on them before applying it.

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Virtual makeup try-on method that enables users to quickly enter the virtual makeup function in a virtual fitting room. The method involves touching a 3D model on the display screen in the virtual fitting room to activate the virtual makeup function. This allows users to easily and quickly access the virtual makeup from the fitting room to try on different makeup looks. The makeup effect is then displayed on the 3D model so the user can view the fitting and makeup together to understand which clothing and makeup combinations suit them best.

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Method for providing augmented makeup services over the web that allows users to try on customized makeup in real time using their own facial geometry. The method involves capturing user's facial images, analyzing the geometry of their face, and generating dedicated 3D models of makeup products that fit their unique face shape. The customized makeup is then superimposed onto the user's live video feed to enhance their appearance.

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Virtual makeup application system that allows remote makeup consultations and virtual makeup application over the internet. It uses 3D facial modeling to enable a makeup artist to apply virtual makeup to a client's facial images in real-time and see the results. The artist's actions are captured and commands are sent to the client's device to apply the virtual makeup. The system involves a makeup application device for the artist and a client device for the client. The artist's device generates a 3D model from client images, lets the artist apply virtual makeup, and sends commands to the client's device to apply the virtual makeup to the images.

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Enhancing the user experience of virtual makeup application on devices like smartphones by allowing users to view the results from different angles. The method involves capturing videos of the user's head, extracting images at multiple angles, applying makeup virtually to one image, then applying it to the user's face in the selected angle view. This provides a more realistic and accurate preview of how the makeup would look from different perspectives.

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Virtual makeup application system that allows users to try on and view makeup in multiple orientations. The system extracts images of a user's face from videos at different angles, converts them into a 3D model, and applies selected makeup virtually. When the user wants to see the virtual makeup from a particular angle, they can select it. This provides a more realistic and immersive virtual makeup experience compared to just viewing from the front.

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Enhanced cosmetic service system that provides customized makeup for users by analyzing their facial features and generating 3D models of user-specific makeup. The system involves capturing user images, analyzing facial geometry, calculating numerical values for facial features, creating personalized makeup models, and applying them to user images. The user can then order and receive their customized makeup. The system allows users to try on and order makeup specifically matched to their face shape and dimensions.

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A makeup application assist device and method that helps users apply makeup in a way that matches their facial features. The device acquires user, target, and adjusted face images. It compares facial features between user and target images to determine which makeup items to use. If user features match target, it uses the original makeup. If not, it uses makeup from the adjusted image for those parts. This allows presenting natural makeup that maintains balance by adapting to user features.

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Smart mirror system that allows users to quickly see the effect of virtual makeup while looking in the mirror and choose the best one. The mirror captures the user's face image and sends it to a separate virtual makeup subsystem. The subsystem analyzes the face, retrieves desired makeup models, and synthesizes the virtual makeup to overlay on the user's face. This lets users see multiple makeup looks in real time and select the one they like best.

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Virtual makeup method, device, and equipment that allows users to try on different cosmetics virtually without needing physical samples. The method involves acquiring user-selected cosmetic data and the user's face image. It then uses a trained universal virtual makeup model to apply the chosen cosmetics to the user's face in the image. The model is trained using a diverse set of makeup images from various brands.

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Method for evaluating facial makeup that provides personalized feedback to users on their makeup application. The method involves evaluating the avatar area of a user's face in an image using a customized model. The evaluation result is then displayed along with the original image. This allows users to see areas needing improvement and suggestions for adjustment. The customized model is trained using personalized annotations from a user's face. By tailoring the evaluation to the user's preferences, it provides more accurate and helpful feedback compared to generic makeup evaluation tools.

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Virtual makeup method to improve authenticity by matching virtual makeup parameters to actual products. The method involves analyzing skin attributes from an initial face image, determining makeup parameters for a target product, and applying those parameters to the initial image to generate a virtual makeup result that better matches the actual product. It allows customizing virtual makeup to accurately simulate the effects of specific products.

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Virtual makeup try-on using facial recognition and AR to allow users to see how makeup products will look on them before buying. It involves extracting facial feature points, creating a 3D model, converting it to 2D, matching makeup resources, rendering in a second camera, and overlaying on the original image.

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Customized semi-permanent makeup recommendation system using virtual experience to reduce anxiety and improve satisfaction with the procedure. The system scans a customer's face using a 3D scanner to extract measurements like eye, nose, mouth sizes and intervals. These measurements are processed to generate a virtual model of the face. The virtual model is then used to simulate and visualize how the semi-permanent makeup would look on the customer's face. This virtual experience allows customers to see the expected outcome before committing to the procedure, reducing anxiety and dissatisfaction with the final result.

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Extracting a user's makeup habits from their own images to provide more realistic and personalized makeup recommendations. The method involves acquiring the user's face in both unmadeup and madeup states, deforming them based on reference face feature points, and extracting the makeup changes. This allows generating makeup materials that match the user's aesthetic preferences. The extracted makeup can be applied to other faces to provide customized makeup recommendations.

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Simulating makeup on a device to preview how cosmetics will look without actually applying them. The method involves using a camera to capture an image of the desired cosmetic product, identifying it, and then superimposing the makeup effect onto a separate captured image of the user's face. This allows users to see how the product will look on them without needing the physical item.

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