Facial Recognition Makeup Pattern Normalization
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Solution Overview
Problem
Facial recognition technology is sensitive to changes in makeup, making it challenging to accurately recognize faces before and after makeup application, especially when different makeup methods are used.
Innovation Solution
A method and apparatus that identify and apply makeup patterns to specific regions of interest (ROIs) in images, generating adjusted images for comparison to ensure robust facial recognition, using a database of candidate patterns to determine similarity and apply appropriate makeup patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional facial recognition is performed based on images, then the technology is convenient and non-contact, but the recognition accuracy deteriorates when makeup patterns differ between images
Solution Approach 1:
The system performs preliminary action by identifying and removing makeup patterns from the first image before facial recognition. The makeup pattern identification unit detects makeup regions and characteristics in advance, and the makeup pattern removal unit eliminates these patterns, creating a normalized first image that matches the makeup condition of the second image, thereby ensuring accurate recognition despite initial makeup differences
Solution Approach 2:
The system applies parameter changes by modifying the visual parameters of the first image through makeup pattern removal. By changing the color, texture, and appearance parameters of makeup regions to match the natural skin state or the makeup state of the second image, the system transforms the first image into a comparable form, resolving the accuracy issue caused by makeup variations
2Reliability
If makeup pattern identification and removal is performed, then recognition accuracy improves, but device complexity increases
Solution Approach 1:
The system divides the facial recognition process into distinct segments: a makeup pattern identification unit that detects makeup regions, a makeup pattern removal unit that eliminates makeup effects, and a facial recognition unit that performs recognition. This segmentation allows each component to specialize in its function, improving overall accuracy while managing complexity through modular design
Solution Approach 2:
The makeup pattern removal unit acts as an intermediary between image acquisition and facial recognition. It mediates the difference in makeup conditions between images by normalizing the first image, enabling accurate recognition without requiring complex adjustments in the recognition algorithm itself
Data Source
AI summary
A facial recognition method includes identifying a first makeup pattern in a region of interest (ROI) of a first image, applying one of the first makeup pattern and a candidate makeup pattern to a ROI of a second image corresponding to the ROI of the first image to generate a third image and recognizing a face based on the first image and the third image.