3D Face Recognition Using Bilateral Symmetry Profile Extraction
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Solution Overview
Problem
Current 3D face recognition methods are computationally expensive and lack accuracy due to noise, expression variance, and incomplete scanning, with existing 3D facial data processing being inefficient and prone to errors from irregular boundaries and occlusions.
Innovation Solution
A method utilizing a 3D triangular facial mesh to extract a bilateral symmetry plane, compute the Symmetry Profile, and establish a Face Intrinsic Coordinate System (FICS) for aligning facial representations, combined with Forehead and Cheek Profiles to create a compact SFC representation for accurate comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D facial data is processed using traditional methods, then comprehensive facial features can be captured, but computational complexity increases and processing time extends
Solution Approach 1:
The patent extracts only the essential bilateral symmetry plane and profile curves from the complete 3D facial surface, removing redundant information while preserving the most discriminative features for recognition. This extraction approach reduces computational complexity by focusing on key geometric characteristics rather than processing all facial surface data.
Solution Approach 2:
The patent creates simplified 2D profile curve representations (symmetry profile, forehead profile, cheek profile) that copy the essential geometric information from the 3D facial surface. These profile curves serve as compact substitutes for full 3D data, enabling efficient comparison and recognition with reduced computational requirements.
2Measurement precision
If complete 3D facial surface data is used for recognition, then recognition accuracy improves, but processing time increases
Solution Approach 1:
The patent extracts only the essential bilateral symmetry plane and profile curves from the complete 3D facial surface, removing redundant information while preserving the most discriminative features for recognition. This extraction approach reduces computational complexity by focusing on key geometric characteristics rather than processing all facial surface data.
Solution Approach 2:
The patent divides the 3D facial surface into three distinct profile segments (symmetry profile, forehead profile, cheek profile) that can be processed independently. This segmentation allows for parallel processing and reduces the overall computational burden compared to processing the complete facial surface as a single unit.
3Reliability
If traditional 3D face recognition methods are used, then facial features can be captured, but errors increase due to noise, expression variance, and incomplete scanning
Solution Approach 1:
The patent deliberately focuses on the bilateral symmetry plane, which represents the symmetric axis of the face. By concentrating on this central symmetric region and the profile curves along it, the method is less sensitive to asymmetric variations caused by facial expressions, partial occlusions, or scanning errors, thereby improving reliability.
Solution Approach 2:
The patent performs preliminary extraction of the bilateral symmetry plane and profile curves before conducting recognition comparisons. This preliminary processing step prepares standardized, noise-resistant representations that are less susceptible to expression variance and scanning imperfections, improving the robustness of subsequent recognition operations.
Data Source
AI summary
There is provided a novel approach for automatic human face authentication. Taking a 3D triangular facial mesh as input, the approach first automatically extracts the bilateral symmetry plane of the face surface. The intersection between the symmetry plane and the facial surface, namely the Symmetry Profile, is then computed. By using both the mean curvature plot of the facial surface and the curvature plot of the symmetry profile curve, three essential points of the nose on the symmetry profile are automatically extracted. The three essential points uniquely determine a Face Intrinsic Coordinate System (FICS). Different faces are aligned based on the FICS. The Symmetry Profile, together with two transversal profiles, namely the Forehead Profile and the Cheek Profile compose a compact representation, called the SFC representation, of a 3D face surface. The face authentication and recognition steps are finally performed by comparing the SFC representation of the faces.