DToF Face Recognition With Fused Lattice Depth Images
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Solution Overview
Problem
Face recognition in face recognition payment systems is not precise enough when performed directly on cropped images, necessitating improved precision and efficiency.
Innovation Solution
A method involving a Dtof sensor to acquire lattice depth images from different angles, followed by fusion processing to create a dense lattice depth image, and subsequent face recognition on this image to enhance precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face recognition is performed directly on the cropped to-be-recognized image, then the processing speed is fast, but the recognition precision is not sufficient
Solution Approach 1:
The patent applies preliminary action by performing depth image acquisition and lattice depth map generation before the actual face recognition process. The system pre-processes the image to create a dense lattice depth map that enhances facial feature information, thereby improving recognition precision while managing complexity through structured preprocessing steps
2Measurement precision
If multiple depth images from different angles are acquired and fused, then the face recognition precision is improved, but the power consumption increases
Solution Approach 1:
The patent applies segmentation by dividing the face image into a lattice structure with multiple depth layers. This segmentation allows the system to process and fuse depth information from different angles more efficiently, improving recognition precision while reducing overall power consumption by focusing computational resources on structured lattice regions rather than entire images
Solution Approach 2:
The patent implements partial action by acquiring depth images from selected angles rather than all possible angles. The system fuses a sufficient number of depth images to achieve high precision face recognition while avoiding the excessive power consumption that would result from capturing and processing depth images from every possible angle
3Measurement precision
If a Dtof sensor is used to acquire lattice depth images, then the face recognition precision is enhanced, but the device complexity increases
Solution Approach 1:
The patent applies mechanics substitution by replacing traditional mechanical depth sensing methods with a Dtof (Direct Time of Flight) sensor. This substitution enables high-precision depth measurement and lattice depth map generation without complex mechanical moving parts, thereby enhancing face recognition precision while actually reducing mechanical device 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
This approach achieves high-precision face recognition with reduced power consumption by using Dtof sensors and fusion processing to improve accuracy and reduce costs.
Implementation Method 1
a Dtof sensor, configured to acquire lattice depth images of a face
Data Source
AI summary
A face image processing method includes: obtaining a plurality of lattice depth images acquired by performing a depth image acquisition on a target face from different acquisition angles; performing a fusion processing on the plurality of lattice depth images to obtain a dense lattice depth image; and performing a face recognition processing on the dense lattice depth image to obtain a face recognition result.