AI-Based Analysis for Hairstyle Recommendations

A hairstyle recommendation system that provides personalized styling suggestions based on a customer's unique characteristics and preferences. The system employs a hybrid approach that combines traditional styling algorithms with advanced biometric analysis, incorporating facial and hair features to generate highly tailored recommendations. The system integrates with facial recognition technology to analyze the customer's facial structure and hair characteristics, then uses this data to generate personalized styling suggestions that are both aesthetically pleasing and functional.

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Diagnosing a user's curly hair type using AI and recommending specific hair care products based on the diagnosis. The system receives user-inputted images of their hair and uses AI models to diagnose curl patterns, hair texture, and shine. It then recommends products and regimens tailored to the user's hair needs. The AI models are trained using curly hair images and can detect coily, curly, kinky, wavy, and straight hair patterns. The system can also provide guides on hair science and care.

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A system that estimates the details of hair treatment required to achieve a desired hairstyle based on user selected images. The system combines the user's face with a selected hair image to create a composite image. It then estimates the specific hair treatment needed to transform the user's actual hair into the composite image using a learned model that links hair images before and after treatment with the treatment steps.

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Synthesizing virtual hairstyles using AI and machine learning to create realistic digital representations of hairstyles. The method employs a combination of facial analysis and AI-driven generation, where the system estimates a user's face shape and hairline, then applies a pre-defined hairstyle template to create a digital version. The AI system uses a GAN architecture to generate the virtual hairstyle, combining multiple iterations of feature point synthesis to achieve natural-looking results.

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Hair service device using deep learning to match customers with salon stylists and recommend salons based on their search queries. The device analyzes a vast database of hair images and user feedback to identify matching hairstyles, then uses AI-driven recommendations to match customers with salons that match their search criteria. This approach enables personalized salon matching through natural language processing and image analysis, rather than relying solely on keyword matching or user feedback.

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Hair style recommendation system that optimizes hairstyle selection by analyzing user-specific characteristics and medical data. The system employs advanced computer vision techniques to extract detailed features from user images, including hairline position, follicle density, and hair texture. These features are then matched against a comprehensive library of hairstyles to determine the most suitable style for each user. The system incorporates 3D modeling capabilities to accurately capture the user's head shape and features, enabling personalized recommendations.

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Recommendation system for hairstyles based on face shape analysis. The system extracts detailed facial features from a complete head image using AI-powered facial feature point extraction, then measures the shape and size of each feature to generate comprehensive facial shape information. This comprehensive shape information is used to recommend hairstyles that match the user's face characteristics. The system incorporates user preferences into the recommendation process by weighting hairstyles based on their similarity to the user's face shape.

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Personalized hairstyle recommendation system that analyzes facial features to match individual characteristics with hair styles. The system extracts facial features from images, analyzes hair characteristics across different regions, and determines the most suitable hairstyle based on matching features. It provides a comprehensive approach to matching hair styles with facial features, enabling customers to find a hairstyle that complements their unique facial structure.

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Beauty recommendation system for individuals with diverse skin tones, hair types, and facial features. The system uses AI-driven deep learning models to analyze user images and determine their face type, hair type, and skin tone. It then recommends personalized makeup styles based on these characteristics, including hair styles, effects, and cosmetics. The system integrates with wearable devices to generate virtual images of recommended styles.

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Intelligent hair styling system that enables personalized hair design through AI-driven matching between customer preferences and stylist capabilities. The system creates a virtual avatar based on customer facial features, then displays a range of hairstyle options that match the avatar's characteristics. Stylists can then select from these options, and the system automatically matches the customer with a suitable stylist based on their preferences. The system evaluates the stylist's availability and pricing before sending the customer a final design and pricing information.

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A system for personalized beauty advice that matches users with complementary beauty solutions based on their hair style. The system analyzes the user's hair style and generates recommendations for matching body decorations, including makeup, nail art, and esthetics, that enhance their overall appearance. The recommendations are calculated based on the user's hair style characteristics, enabling users to discover new beauty combinations that complement their natural features.

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AI hairstyle matching system that optimizes virtual hairstyles based on individual characteristics and hair growth patterns. The system analyzes user characteristics, including hair follicle distribution, growth status, and scalp health, to create personalized virtual profiles. It then matches these profiles with a library of virtual hairstyles, predicting potential outcomes based on predicted growth patterns. The system enables users to select from these matched hairstyles, with AI-driven evaluation and feedback mechanisms to refine their preferences.

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Image processing method and device that enables automatic virtual hairstyle generation by analyzing hairline layout features in a target image. The method identifies the target image's face detection area, extracts the hair region, determines hairline layout features, and matches virtual hairstyles to the hair region using these features. This approach enables precise virtual hairstyle matching by leveraging the hairline's spatial distribution patterns.

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AI-powered smart mirror system that automatically generates personalized hairstyles through facial analysis and trend-based matching. The system captures detailed facial features using visible and infrared cameras, analyzes them to extract key points, and uses this data to identify the user's ideal hairstyle. It then searches for and displays matching hairstyles from its vast database, allowing users to seamlessly transition between virtual and real-world styles without the need for separate consultations.

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Recommendation of hairstyles based on real-time hair condition analysis. The system analyzes the user's hair condition after treatment and estimates the optimal hairstyle based on the current hair length and growth pattern. It then selects a hairstyle that matches the estimated condition, taking into account variations in hair growth patterns across different parts of the head. The system presents the recommended hairstyle at the optimal time for the user's current hair condition, ensuring a personalized match.

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Self-hairstyling device with an unmanned kiosk function that enables users to style their hair remotely through AI-driven recommendations and real-time video displays. The device features a hair dryer and curling iron, with a built-in camera capturing the user's face. An AI algorithm analyzes the user's face shape, hair length, and current hairstyle to provide personalized styling recommendations. The device continuously monitors the user's progress and displays the styling process in real-time, allowing users to follow their customized look. The system also includes a payment terminal for credit card transactions, a vending machine for hair care products, and an ultraviolet sterilization unit for device maintenance.

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A personalized hairstyle consulting system that enables customers to discover customized hairstyles tailored to their unique face shape, hair characteristics, and desired aesthetic. The system uses advanced 3D facial analysis to generate a personalized 3D model of the customer's face, which is then used to create a range of hairstyle options. Customers can input their desired hairstyle, hair length, texture, and bangs, and the system generates multiple customized hairstyles that match their face shape and hair characteristics. The system provides expert consultation and transmission of the recommended hairstyles to the customer's terminal, enabling a comprehensive and personalized hairstyle solution.

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A hairstyle navigation service system and method using AI that enables personalized hair styling by matching customers with skilled stylists and providing customized styling advice through a user interface. The system integrates customer preferences, hair condition information, and desired styles into a comprehensive service, then connects customers with trained stylists who can deliver precise, expertly crafted hairstyles. The system employs advanced AI algorithms to analyze customer input and match it with suitable stylists, while also providing customers with detailed styling guidance and recommendations through a user-friendly interface.

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Hair style recommendation system that provides personalized virtual hair styling using AI-driven bald hair transformation and realistic hair simulation. The system employs a multi-stage approach: first, it converts a user's bald head image into a virtual hair model through an AI algorithm. Then, it generates realistic hair styles based on the user's facial features, hair type, and personal preferences. The system integrates facial biometric analysis and user input to provide accurate and customized virtual hair simulations.

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Predictive styling for individuals seeking aesthetic enhancements through personalized hair recommendations. The system analyzes facial images and user data to generate customized hairstyle suggestions based on both objective appearance metrics and user preferences. This approach enables users to discover flattering styles that objectively complement their features, rather than relying solely on subjective preferences. The system integrates with hair salons to deliver personalized styling recommendations to customers.

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Method for personalized hair style visualization through 3D modeling and virtual try-on. The method captures detailed images of a subject's head and creates virtual models based on their facial features and hair characteristics. It then determines the most suitable hair style based on these characteristics, selects the corresponding hair style changing means, and displays the virtual model with the selected style. The method incorporates hair loss analysis to refine the style selection process.

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A computer data mining method for discovering personalized hairstyle recommendations based on large-scale online data. The method collects hairstyles from various character models across the web, extracts their unique features, and analyzes these features to identify patterns that can be used to create personalized hairstyle recommendations.

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A beauty salon support server, user terminal program, and beauty salon terminal program that enables users to select from a vast library of hairstyles based on attributes like hair length, texture, and style. The system stores captured images of hairstyles applied by beauticians and associates them with specific attributes. When a user selects a hairstyle, the system retrieves the corresponding image from the database, displays it on the user's terminal, and allows them to edit the hairstyle. The edited image is then transmitted back to the salon, where it is used to create a personalized recommendation for the user. This approach enables users to explore new hairstyles without having to physically visit the salon, while still receiving expert guidance and personalized recommendations.

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Intelligent haircut assistant system that enables precise and personalized haircuts through machine learning-based analysis of user input and real-time head movements. The system employs a comprehensive library of hairstyle images, a real-time camera module capturing user facial and hair characteristics, and a sophisticated preprocessing module that matches user input with hairstyle data. The system then generates a customized haircut plan based on user preferences and real-time head movements, with automatic adjustments for optimal results.

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A system for proposing personalized hairstyle treatments that matches customer preferences. The system analyzes customer input and generates customized treatment plans through a combination of natural language processing and machine learning algorithms. It enables hairdressers to provide more targeted and effective treatments by automatically generating treatment plans based on customer preferences.

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Providing personalized hair salon services through a server-based system that analyzes users' hair images and determines customized hairstyles based on their face shape, hair texture, and scalp conditions. The system stores user history and receives external hair images, then uses AI to match users with similar hairstyles based on their facial features. The system generates personalized hairstyle recommendations, including price information, and displays them to the user through a user interface.

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Hair recommendation system that enables personalized virtual hair styling through real-time mapping of virtual hair models onto a user's face. The system separates the face from the input image, extracts facial features and color characteristics, and combines them to create a unique virtual hair model. This virtual model is then applied to the user's face in real-time, allowing for instant virtual styling without the need for physical haircuts. The system uses machine learning algorithms to analyze the user's face and hair characteristics to recommend the most suitable virtual hair model.

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Intelligent hairstyle design system that automatically matches haircuts with a person's face shape, enabling personalized styling options. The system employs advanced face shape recognition algorithms to analyze facial features and determine the most flattering hairstyle configuration. This approach eliminates the need for manual styling consultations, allowing users to discover their ideal haircut without the need for professional consultations.

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A hairstyle recognition system that improves accuracy by leveraging pre-trained models to extract hair regions from user images before applying traditional classification. The system employs a single-attribute recognition model for hair region detection, followed by a pre-trained model that classifies the hair region into predefined hairstyle categories. This approach enables efficient identification of hairstyles by focusing on the hair region rather than the entire image, while the pre-trained model handles the detailed hairstyle classification. The system can be integrated into various applications, including beauty and identity recognition systems, where accurate hairstyle identification is critical.

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Digital imaging method to analyze user body images to determine hair density and provide personalized grooming recommendations. The method involves training a hair density model using images of users with known hair densities. The model analyzes new user images to determine their hair density. Based on the density, it recommends products, behaviors, and styles tailored to the user's hair.

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Generating personalized hair care recommendations through AI-driven optimization of hair quality parameters. The method analyzes user images to identify hair quality issues, then applies AI-driven optimization techniques to improve hair health. It extracts hair objects from images, extracts hair quality parameters, and generates optimization suggestions based on these parameters. The method presents personalized recommendations through interactive simulations, allowing users to explore hair care options that address specific quality concerns.

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Extracting images with similar hairstyles through feature-based matching. The system generates hair color and hairstyle features from captured images, then combines these features to create a new feature space. It then searches through a database of images to find the original image that generated the combined feature space, effectively matching the hairstyle. This approach enables automatic hairstyle matching across diverse individuals.

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A hair care method that enables personalized hair style recommendations through machine learning and social network analysis. The method generates a comprehensive user profile based on hair data, facial features, and treatment history, then creates a virtual "style avatar" that matches the user's preferences. The avatar is then used to generate a wide range of virtual hairstyles through rendering algorithms, with each style rendered from multiple perspectives. Users can then vote on their preferred style, and the system matches them with a salon capable of delivering the recommended style.

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Method for enhancing hairstyle visualization through personalized matching and 3D model integration. The method enables hairdressers to accurately match clients' facial features with recommended hairstyles by analyzing facial images and 3D models. The system provides a comprehensive preview experience by stitching the client's facial model with the recommended hairstyle, allowing for precise visualization of the match. This approach enables hairdressers to better understand their clients' preferences and deliver more accurate, personalized styling recommendations.

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Augmenting mobile device images with personalized hairstyle options using computer vision and machine learning. The method generates a 3D model of the user's body from multiple images, analyzes facial landmarks to create a user-specific framework, and applies customized hairstyle configurations to the model. The system enables users to select and apply personalized hairstyles from a comprehensive library, with features like automatic path optimization and real-time analysis.

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System and method for providing hairstyle recommendations through smart mirror technology that enables personalized styling advice by leveraging user data from multiple sources. The system analyzes user images, social media activity, and facial recognition data to identify matching styling patterns, then generates recommendations based on those patterns. This approach provides a more comprehensive understanding of a customer's hair preferences compared to traditional consultation methods, enabling more accurate styling recommendations.

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Hair styling system that enables hair stylists to create personalized hairstyles based on specific attributes. The system classifies hair styles into predefined structural modules, each corresponding to distinct attributes like length, shape, level, and texture. These modules are then divided into multiple styles, allowing stylists to select the most suitable design based on customer preferences. The system automatically matches the selected style with corresponding hairstyle images from a library, ensuring accurate design execution.

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A method for personalized hairstyle recommendation using deep learning-based computer vision. The method employs a ResNet neural network to predict hairstyle characteristics such as hair length, width, and facial proportions. These predictions are then used to generate augmented reality hair trials that allow users to visualize their desired hairstyle before making a final decision. The method enables users to explore multiple hairstyle options in a realistic and interactive manner, with personalized recommendations based on their specific facial characteristics.

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Intelligent hairstyle recommendation system that enables personalized styling through 3D modeling and neural network analysis. The system employs a neural network architecture to analyze facial features and predict optimal hairstyle combinations based on user characteristics. The system integrates with Unity for seamless integration with mobile applications, and provides a user interface for selecting hairstyles. The neural network model is trained on a comprehensive dataset of facial features and hairstyles, enabling accurate predictions of suitable styles for individual users.

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Processing facial image hairstyles for mobile terminals to enable personalized hairstyle matching through facial image processing. The method and system analyze facial features to determine hairstyle compatibility, allowing users to select and apply hairstyles from a library without needing to physically visit a barber. The system employs advanced facial analysis algorithms to predict hairstyle suitability based on facial characteristics, enabling users to confidently try new hairstyles without the need for in-person consultations.

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Conditional Variational Autoencoder (CVAE) for generating diverse hairstyle and hair color variations from a single input image, enabling personalized styling recommendations. Unlike traditional VAEs that predict complete person appearances, CVAE generates conditional distributions of hairstyle and hair color attributes, allowing customers to explore multiple variations without generating complete person images. This approach enables targeted styling recommendations by conditioning on specific attributes, rather than generating complete person appearances.

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A method and system for personalized hairstyle matching through computer vision analysis of facial features. The method involves acquiring a target face image, extracting facial features, and using machine learning algorithms to predict optimal hairstyle combinations based on the individual's face shape, hair texture, and personal preferences. The system enables users to upload their target face images and receive personalized hairstyle recommendations through computer vision analysis of facial features.

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A customer-autonomous haircut experience system that enables personalized, 360-degree virtual haircuts through augmented reality (AR) technology. The system uses 360-degree head imaging to accurately capture the user's facial structure and hairstyle preferences. AR software then generates a virtual haircut based on these inputs, allowing users to preview and adjust the style before the actual cut. This approach eliminates the traditional limitations of verbal or pattern-based styling, enabling customers to achieve their desired look with precision.

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Intelligent hairstyle and presentation recommendation system that leverages machine learning to match users with personalized styling options. The system creates a comprehensive database of hairstyles and facial features, trains a deep learning model to analyze and match these elements, and generates customized presentation recommendations based on user preferences. This approach enables users to discover new styles and presentations that align with their unique features and preferences.

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A CNN-based hairstyle recommendation system that leverages computer vision to predict optimal hairstyles for users. The system employs a convolutional neural network (CNN) architecture to analyze facial features and predict the most flattering hairstyle based on user input. The CNN extracts facial features through convolutional layers, applies a series of efficient convolutional kernels to reduce redundant calculations, and uses a connection layer to establish complex mapping relationships between input and output. The system then processes the extracted features using ROI analysis to optimize contour extraction, and trains the network using supervised learning to achieve accurate hairstyle recommendations.

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Intelligent hairstyle matching system that automatically matches a person's hairstyle based on their facial features. The system employs a face scanning unit to capture the person's facial structure, a feature data processing unit to analyze the facial features, and a hairstyle matching interface to generate personalized hairstyle recommendations. The system utilizes a comprehensive database of hairstyles to match the person's facial characteristics with suitable hairstyles, enabling them to achieve a hairstyle that accurately reflects their natural features.

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A system for personalized hair styling that enables local modifications through digital means. The system comprises a face scanning unit, feature data processing unit, hairstyle matching interface, and a hairstyle database. The system allows users to select a hairstyle through a digital image, but with the added capability to make targeted adjustments to the hairstyle through a separate interface. This enables users to achieve a customized look that matches their unique features and preferences, rather than relying solely on the initial hairstyle selection.

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Hair analysis system that uses deep learning to automatically assess hair condition through image analysis. The system captures user images, trains a neural network to identify hair characteristics from these images, and analyzes the user's hair condition based on the trained features. The system provides personalized recommendations for hair care and styling based on the analysis, including product recommendations, styling advice, and scalp health insights.

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Hair styling method that enables personalized hair design through face analysis. The method uses advanced facial analysis to create customized hairstyles that match the user's face shape, rather than relying on generic hair style libraries. By analyzing the user's facial features, the system generates unique hairstyle recommendations that are tailored to their specific face characteristics, resulting in more accurate and personalized styling results.

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Hair styling service method and apparatus that recommends personalized hairstyles based on user characteristics. The method combines user profile data with image analysis to predict optimal hairstyle options. It categorizes users by age, personality, profession, and head shape, then recommends hairstyles that align with these characteristics. The service generates a composite image of the recommended hairstyle and price information for the service. This approach enables users to find personalized hairstyles that match their unique characteristics without requiring multiple style selections.

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