3D Model Generation from 2D Images for Facial Recognition
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Solution Overview
Problem
Current facial recognition systems relying on two-dimensional databases face limitations due to variations in equipment and environment, making it challenging to achieve accurate recognition, and transitioning to three-dimensional databases is costly and impractical due to the need for new infrastructure and re-sampling of existing data.
Innovation Solution
A method and system that converts existing two-dimensional image databases into three-dimensional model databases by processing two-dimensional images to generate estimated three-dimensional models, allowing for object identification independent of the image source, including the use of three-dimensional models for comparison with two-dimensional images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If three-dimensional model databases are created from scratch using specialized equipment, then recognition accuracy is improved, but infrastructure cost and device complexity increase significantly
Solution Approach 1:
The patent transforms two-dimensional image data into three-dimensional model representations by adding depth information through estimated 3D models. This dimensional transformation allows the system to leverage existing 2D databases while achieving 3D recognition capabilities, thereby improving accuracy without requiring complete infrastructure replacement
Solution Approach 2:
Instead of creating new 3D databases from scratch, the patent generates estimated three-dimensional models as virtual copies derived from existing two-dimensional images. These estimated models serve as sufficient representations for recognition purposes, avoiding the need for expensive specialized 3D scanning equipment and infrastructure
2Measurement precision
If existing two-dimensional databases are converted to three-dimensional models, then recognition accuracy under various conditions is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preprocessing to generate estimated three-dimensional models from two-dimensional images in advance, before the actual recognition task. These pre-generated 3D models are stored and can be quickly retrieved and compared during recognition operations, reducing real-time processing delays
Solution Approach 2:
The system transforms image data from two-dimensional parameters to three-dimensional parameters by generating estimated 3D models. This parameter transformation enables more robust recognition under varying conditions while the estimation techniques keep computational requirements manageable
3Device complexity
If two-dimensional comparison methods are used, then existing infrastructure is maintained, but recognition accuracy deteriorates under different equipment and environmental conditions
Solution Approach 1:
The patent creates a hybrid system that maintains compatibility with existing two-dimensional image databases and infrastructure while incorporating three-dimensional model processing capabilities. The system can handle both 2D images and their corresponding 3D estimated models, providing multi-functional recognition that works across different equipment and environmental conditions
Data Source
AI summary
A method for identifying an object based at least in part on a reference database including two-dimensional images of objects includes the following steps: (a) providing a three-dimensional model reference database containing a plurality of estimated three-dimensional models, wherein each estimated three-dimensional model is derived from a corresponding two-dimensional image from the two-dimensional reference database; (b) sampling at least one image of an object to be identified; (c) implementing at least one identification process to identify the object, the identification process employing data from the three-dimensional model reference database.