AR Facial Makeup Generator Using IFM and SDF Primitives
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Solution Overview
Problem
Developing augmented reality (AR) content generators for facial makeup products is challenging due to the need for collecting and generating various creative assets, which can be time-consuming and complex, especially in providing standard data formats to enhance the onboarding and development process.
Innovation Solution
The introduction of an internal facial makeup format (IFM format) that enables AR content items for facial makeup looks to be defined and constructed using individual primitive shapes, which can be combined to create specific looks, utilizing procedural techniques and signed distance fields (SDFs) for efficient mask generation and shading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional methods are used to collect and generate creative assets for AR facial makeup content generators, then comprehensive asset coverage can be achieved, but the development process becomes time-consuming and complex
Solution Approach 1:
The patent segments complex facial makeup looks into individual primitive shapes (sdf primitives) that can be independently defined and combined. Instead of collecting complete makeup looks as assets, the system breaks them down into fundamental geometric components that can be procedurally assembled, significantly reducing the time and complexity of asset creation while maintaining comprehensive coverage of various makeup styles.
Solution Approach 2:
The patent establishes a standardized internal facial makeup format (IFM) that pre-defines the structure and composition rules for facial makeup content. By setting up this framework in advance with predefined primitive shapes and combination rules, the system enables rapid generation of diverse makeup looks without requiring time-consuming manual asset creation for each specific look.
2Manufacturing precision
If manual asset creation methods are used, then high fidelity facial makeup looks can be achieved, but the process becomes complex and difficult to scale
Solution Approach 1:
The patent implements a procedural generation system where the AR content generator automatically creates facial makeup looks by combining primitive shapes according to the defined IFM. The system serves itself by algorithmically generating high-fidelity makeup patterns without requiring manual asset creation, thereby maintaining precision while eliminating the complexity and difficulty of scaling the asset creation process.
3Adaptability or versatility
If diverse facial makeup looks are created using traditional asset collection, then variety and adaptability are achieved, but the onboarding and development process becomes cumbersome
Solution Approach 1:
The patent enables diverse facial makeup looks by varying parameters of the primitive shapes (such as size, position, orientation, and combination rules) rather than creating separate assets for each look. This parameter-based approach allows the system to generate a wide variety of makeup styles by adjusting numerical parameters, making the onboarding and development process much easier while maintaining high adaptability and versatility.
Data Source
AI summary
The subject technology determines at least one primitive shape based on at least one graphical element in an augmented reality (AR) facial pattern. The subject technology generates a JavaScript Object Notation (JSON) file using at least one primitive shape. The subject technology generates internal facial makeup format (IFM) data using the JSON file.