AI Face Visualization for Cosmetic Treatment Prediction
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Solution Overview
Problem
Current methods for visualizing the effects of cosmetic and medical treatments on facial appearance are inadequate, as they fail to accurately predict how others perceive the changes, leading to difficulties in selecting treatments that optimize appearance and may result in undesirable outcomes.
Innovation Solution
A method using a dataset of face visuals and extracted property data, combined with deep learning, to generate computer-modified visuals of desired facial changes based on selected characteristics, allowing users to choose specific traits to enhance or reduce, such as attractiveness, youthfulness, or competence, and providing recommendations for necessary treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a specialist inspects the face and proposes treatments based on personal knowledge, then treatment recommendations are provided, but it is difficult for the person to understand the possible visual effects and effects on first impression
Solution Approach 1:
The patent creates a digital copy of the person's face using facial recognition technology to generate a virtual model. This copy allows visualization of treatment effects without altering the actual face, enabling the person to see predicted outcomes before undergoing real treatments. The system generates before-and-after comparisons by applying treatment effects to the digital face model.
Solution Approach 2:
The patent introduces an artificial intelligence system as an intermediary between the specialist's recommendations and the person's understanding. The AI analyzes facial features, predicts treatment outcomes, and generates visualizations that bridge the gap between medical expertise and patient comprehension. This intermediary translates complex medical concepts into visual representations.
2Ease of operation
If the user selects anatomical areas and treatments independently, then the process is simplified, but the overall attractiveness of the user may be compromised due to lack of professional guidance
Solution Approach 1:
The patent implements a feedback mechanism where the AI system evaluates the user's selected treatment combinations and provides feedback on their effectiveness. The system analyzes whether the selected treatments will achieve the desired aesthetic goals and may suggest modifications to optimize outcomes. This feedback loop ensures that even though users select treatments independently, the final plan maintains professional quality standards.
Solution Approach 2:
The patent creates a dynamic interaction where the system adapts to user preferences while maintaining professional guidance. The AI adjusts its recommendations based on the user's responses to questions about desired changes, creating a flexible yet reliable treatment planning process that balances user autonomy with expert oversight.
3Measurement precision
If traditional methods are used to assess facial attractiveness, then manual evaluation is simple, but the prediction of how others perceive facial changes is inaccurate
Solution Approach 1:
The patent replaces manual visual assessment with an artificial intelligence system that uses computer vision and machine learning algorithms. The AI analyzes facial features, skin conditions, and anatomical structures with precision beyond human capability. The system processes multiple parameters simultaneously to predict how facial changes will be perceived by others, providing more accurate measurements than traditional manual evaluation.
Data Source
AI summary
A data set of visuals of faces and extracted face property data are generated and linked to face characteristics data provided by a representative set of humans that rate the visuals of these faces with respect to their face characteristics. Further face property data of these visuals of faces is extracted and together with the generated data set used to train an artificial intelligence. The artificial intelligence is used to analyse a visual of the person's face and generate a data set of modifications based on a selected desired characteristic(s) and modifications achievable by at least one cosmetic and/or medical treatment. The visual of the face of the person is modified based on the data set of modifications and the computer-modified visual of the desired face of the person with the modification of the face achievable by the least one proposed cosmetic and/or medical treatment is generated and displayed.