AI Hair Density Analysis for Shaving Feedback
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Solution Overview
Problem
Users with high hair density face challenges in achieving a close shave without skin irritation due to the lack of accurate shaving techniques and equipment, as existing razors and products do not provide sufficient feedback or guidance based on individual hair density, leading to incorrect product purchases and unpleasant shaving experiences.
Innovation Solution
A digital imaging system and method that analyzes pixel data from user images to determine hair density, using a trained AI model to recommend suitable products and techniques, allowing users to submit images for processing on imaging servers or locally on mobile devices, providing product recommendations and graphical feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users with high hair density perform multiple shaving strokes with increased pressure to achieve a close shave, then the closeness of shave is improved, but skin irritation and skin cuts increase
Solution Approach 1:
The patent applies feedback by using image analysis technology to capture and analyze the user's hair density in real-time. The system processes images of the shaving area, determines hair density values, and provides feedback guidance to the user on the appropriate pressure to apply. This closed-loop feedback mechanism enables users to adjust their shaving technique dynamically, achieving close shaves without excessive pressure that causes skin irritation.
Solution Approach 2:
The patent replaces the traditional mechanical trial-and-error shaving approach with an optical and computational system. Instead of relying on users to manually judge hair density and adjust pressure through experience, the system uses image capture devices, pixel analysis algorithms, and computational processing to objectively measure hair density and provide quantitative guidance, substituting mechanical intuition with optical measurement and computational analysis.
2Adaptability or versatility
If users purchase various shaving razors and products without knowing their hair density, then product variety is available, but incorrect product selection leads to unpleasant shaving experiences
Solution Approach 1:
The patent enables self-service by allowing users to independently determine their own hair density using the image analysis system. Users capture images of their shaving areas, and the system automatically processes these images to generate hair density values and personalized product recommendations. This eliminates the need for professional assessment and empowers users to make informed product selections based on objective measurements of their own hair characteristics.
Solution Approach 2:
The patent introduces an intermediary system that bridges the gap between users and shaving products. Rather than users directly selecting products from vast varieties without guidance, the image analysis system acts as an intermediary that measures hair density, processes this information, and translates it into personalized product recommendations. This intermediary layer filters the overwhelming product variety into tailored suggestions matched to individual user characteristics.
3Device complexity
If existing shaving systems do not provide feedback on hair density, then system simplicity is maintained, but users lack guidance for making prudent grooming choices
Solution Approach 1:
The patent applies parameter changes by transforming visual information from images into quantitative hair density parameters. The system captures images, extracts pixel data, and converts this visual information into numerical hair density values that can be objectively analyzed and used for guidance. This parameter transformation enables the system to provide concrete, measurable feedback about hair density while maintaining a relatively simple overall architecture based on established image processing techniques.
Data Source
AI summary
Artificial intelligence based systems and methods are described for analyzing pixel data of an image of a user's body for determining a hair density value of the user's hair. An example method includes aggregating a plurality of training images of a plurality of users' bodies, and training a hair density model operable to output a hair density value. The example method may further include receiving an image of a user comprising pixel data of a portion of the user's body or body area, and analyzing, by the hair density model, the image to determine a user-specific hair density value of the user's hair. The example method may further include generating a product recommendation, wherein the product is designed to address a feature identifiable within the pixel data of the user's body or body area.