3D Face Chart Lighting Intensity Adjustment
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Solution Overview
Problem
Current systems fail to generate realistic three-dimensional (3D) face charts that accurately depict a user's facial features, which hinders the effective selection and application of cosmetic products.
Innovation Solution
A computing device processes images of a user's face to identify facial features, predict skin tone, and adjust lighting intensity in a 3D model, generating a target face image that enhances the stereoscopic effect by superimposing the 3D model onto a 2D face chart, using machine-learning algorithms and physically based rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a 2D face chart is used to depict facial features, then the system is simple to implement, but the three-dimensional effect and realism are insufficient
Solution Approach 1:
The patent transitions from a two-dimensional face chart to a three-dimensional representation by introducing depth information and spatial relationships. The system generates a 3D face model with proper lighting and shadow effects, transforming the flat 2D depiction into a volumetric representation that provides realistic depth perception while maintaining computational feasibility through parameterized modeling approaches.
Solution Approach 2:
The system adjusts lighting parameters including intensity, direction, and color temperature to create realistic illumination effects on the 3D face model. By dynamically modifying these optical parameters based on environmental conditions and cosmetic product properties, the system achieves photorealistic rendering without requiring complex physical lighting setups.
2Illumination intensity
If lighting intensity is increased to enhance 3D effect, then the stereoscopic effect is improved, but the skin tone prediction accuracy may deteriorate due to shadow and highlight interference
Solution Approach 1:
The system performs skin tone prediction before applying intense lighting effects for 3D visualization. By first analyzing the original image under neutral lighting conditions to accurately determine skin tone characteristics, and then separately rendering the 3D model with enhanced lighting, the system avoids the interference of shadows and highlights on color measurement while still achieving realistic visual presentation.
Solution Approach 2:
The system dynamically adjusts lighting intensity based on the measurement stage. During skin tone analysis, lighting is kept neutral and consistent to ensure accurate color measurement. During 3D visualization, lighting intensity is increased to enhance depth perception. This dynamic adaptation allows the system to optimize for the current task requirement.
Data Source
AI summary
A computing device obtains an image depicting a face of a user. The computing device identifies facial features in the image and extracts characteristics of the facial features in the image. The computing device generates a two-dimensional (2D) face chart based on the facial feature characteristics. The computing device predicts a skin tone of the user's face depicted in the image of the user and changes color in a color map of a predefined three-dimensional (3D) model based on the predicted skin tone. The computing device selects a predefined environment map based on characteristics in the image depicting the face of the user and generates a target face image based on the predefined 3D model.