Personalized Makeup Recommendation System Using Facial Analysis

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Solution Overview

Problem

Consumers face challenges in achieving professional makeup results due to the wide selection of cosmetic products for different facial features, and existing online tutorials do not provide tailored makeup effects for individual facial characteristics.

Innovation Solution

A computing device generates digital images depicting makeup trends, analyzes them using a deep neural network to extract target attributes, constructs a database of makeup recommendations, and merges recommendations based on facial similarity to provide personalized makeup suggestions, allowing virtual application of selected effects.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If online makeup tutorials are used, then makeup effects are available, but they are not tailored to individual facial characteristics

Engineering Contradiction:

Improvetailoring to individual facial characteristicsVSAvoidsystem complexity for facial analysis

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary facial analysis by extracting facial features and characteristics from user-uploaded images before generating makeup recommendations. This preliminary action enables personalized recommendations without requiring complex real-time analysis during the makeup application process.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates a digital representation or copy of the user's facial features by analyzing uploaded images and storing extracted attributes. This digital copy is then used to generate personalized makeup recommendations without needing the physical presence of the user's face during recommendation generation.

Inventive Principle:

Principle #26Copying

2Adaptability or versatility

If a wide selection of cosmetic products is provided, then more options are available, but it becomes challenging to achieve professional results

Engineering Contradiction:

Improveproduct selection varietyVSAvoidease of achieving professional results

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system provides personalized makeup recommendations by matching specific cosmetic products to specific facial features and characteristics. Instead of presenting a overwhelming wide selection, the system curates a targeted subset of products that are locally optimized for the user's unique facial attributes, making professional results more achievable.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system uses feedback from facial analysis results to guide product recommendations. By analyzing facial features and using this feedback to select appropriate makeup products, the system simplifies the decision-making process while maintaining access to a wide product selection, thereby improving ease of operation.

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If makeup recommendations are generated from multiple sources, then diversity of suggestions is improved, but redundancy increases

Engineering Contradiction:

Improvediversity of makeup suggestionsVSAvoidnumber of recommendations

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system merges multiple sets of makeup recommendations obtained from different facial features or analysis methods into a unified set of suggestions. By combining and deduplicating recommendations, the system maintains diversity of suggestions while reducing redundancy, presenting a refined set of unique makeup recommendations to the user.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS11253045B2Systems and methods for recommendation of makeup effects based on makeup trends and facial analysis

Publication Date: 2022.02.22 PERFECT MOBILE CORP

AI summary

A computing device generates a collection of digital images depicting makeup effects representing makeup trends, analyzes the collection of digital images, and extracts target attributes. The computing device constructs a database of makeup recommendation entries comprising the collection of digital images and extracted attributes and receives a query request from a user comprising an image of the user's face. The computing device queries the database and obtains a first number of makeup recommendations. The computing device merges makeup recommendations among the first number of makeup recommendations to generate a second number of makeup recommendations and displays at least a portion of the second number of makeup recommendations and receiving a selection from the user. The computing device performs virtual application of a makeup effect corresponding to the selection.