Hybrid Face Liveness Detection via 3D Structured Light and Interactive Analysis
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Solution Overview
Problem
Current face liveness detection technologies are ineffective against online face verification attacks such as synthetic, copy, and mask attacks, which compromise user information security.
Innovation Solution
An AI-based face recognition method that combines interactive liveness detection and 3D structured-light liveness detection functions, using color and depth video frames to verify the presence of a live face, thereby resisting synthetic, copy, and mask attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D structured-light liveness detection is used, then defense against synthetic and copy attacks is improved, but the system cannot effectively defend against mask attacks
Solution Approach 1:
The patent combines 3D structured-light liveness detection with interactive liveness detection to create a hybrid system. The 3D structured-light component handles synthetic and copy attacks by analyzing depth information and light reflection patterns, while the interactive liveness detection component handles mask attacks by verifying real-time facial movements and expressions. This merging of two different detection approaches allows the system to defend against multiple attack types simultaneously.
2Reliability
If interactive liveness detection is used, then defense against mask attacks is improved, but the system cannot effectively defend against synthetic and copy attacks
Solution Approach 1:
The system integrates interactive liveness detection that monitors real-time facial interactions and movements with 3D structured-light detection. The interactive component verifies that the user is physically present and responding to stimuli, which prevents mask attacks. Meanwhile, the 3D structured-light component provides depth mapping and surface analysis to detect synthetic and copy attacks. The fusion of these two detection mechanisms creates comprehensive protection across all attack vectors.
3Reliability
If multiple liveness detection functions are combined, then comprehensive defense against all attack types is improved, but device complexity increases
Solution Approach 1:
The patent implements a unified liveness detection system that performs multiple detection functions through a single integrated architecture. The system uses a common processing framework that can switch between or combine 3D structured-light analysis and interactive liveness detection based on the detected attack type. This multi-functional design allows the system to maintain comprehensive security coverage while avoiding the need for completely separate detection systems for each attack type, thereby reducing overall complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The combined approach effectively defends against synthetic, copy, and mask attacks, enhancing the accuracy of liveness verification and ensuring comprehensive user information security.
Implementation Method 1
A structured-light camera is used to emit uniformly spaced lights that are in a stripe shape to a target. If the target is a real live face, due to the 3D structure of the face, the reflected lights in the stripe shape inevitably have inconsistent intervals.
Data Source
AI summary
An artificial intelligence (AI)-based face recognition method includes: obtaining n groups of input video frames, at least one group of video frames including a color video frame and a depth video frame of a target face, n being a positive integer; invoking an interactive liveness detection function to recognize the color video frames in the n groups of video frames; invoking a second three-dimensional (3D) structured-light liveness detection function to recognize the depth video frames in the n groups of video frames; and determining, in response to both detection results of the interactive liveness detection function and the 3D structured-light liveness detection function indicating that a type of the target face being a liveness type, that the target face is a live target face.