Biometric Embedding Transformation for Cross-Hardware Enrollment
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Solution Overview
Problem
Existing biometric systems require users to perform enrollment processes on each hardware configuration, which is inconvenient and costly, especially as the number of users increases, due to differences in data acquisition and processing across various hardware configurations.
Innovation Solution
A system that propagates representation data from one hardware configuration to another using trained unidirectional transformer networks, allowing users to enroll once and maintain compatibility across different hardware configurations by transforming native representation data into transformed representation data for use with other configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users enroll on multiple hardware configurations, then identification accuracy is improved, but time consumption and operational costs increase
Solution Approach 1:
The system performs preliminary transformation of representation data from a first hardware configuration to a second hardware configuration during the initial enrollment process. This preliminary action ensures that when users later use different hardware configurations, their biometric data is already compatible, eliminating the need for repeated enrollment and reducing time consumption while maintaining identification accuracy.
Solution Approach 2:
The patent introduces representation data transformation as an intermediary mechanism between different hardware configurations. The transformation process converts biometric representation data from one hardware configuration's data space to another's, enabling seamless cross-compatibility without requiring users to re-enroll on each device, thus resolving the contradiction between accuracy and time cost.
2Adaptability or versatility
If users enroll on multiple hardware configurations, then hardware compatibility is improved, but operational costs increase
Solution Approach 1:
The system implements a universal representation data transformation framework that enables a single enrollment to work across multiple hardware configurations. By transforming representation data from one configuration to another during initial setup, the system achieves multi-configurational compatibility without requiring separate enrollment processes for each device, thereby reducing operational costs while improving hardware adaptability.
Solution Approach 2:
The representation data transformation acts as an intermediary that bridges different hardware configurations. This intermediary mechanism allows the system to achieve broad hardware compatibility through a single enrollment process, eliminating the need for repeated enrollments on different devices and thus reducing operational costs while enhancing versatility.
3Ease of operation
If representation data is transformed between hardware configurations, then enrollment convenience is improved, but system complexity increases
Solution Approach 1:
The patent extracts the transformation logic into a separate, dedicated module that handles representation data conversion between hardware configurations. By isolating this complex transformation process into a specialized component, the system maintains simplicity in the user-facing enrollment process while managing the necessary complexity internally, thus improving enrollment convenience without excessively increasing overall system complexity.
Solution Approach 2:
The transformation module serves as an intermediary layer that handles the complexity of cross-configurational data compatibility. This intermediary approach allows the system to maintain simple, user-friendly enrollment processes while managing the inherent complexity of data transformation between different hardware configurations in a controlled manner.
4Adaptability or versatility
If multiple hardware configurations are supported, then system versatility is improved, but data processing time increases
Solution Approach 1:
The system performs representation data transformation in advance during the enrollment phase, rather than in real-time during identification. This preliminary action pre-processes and stores transformed representation data for multiple hardware configurations, enabling rapid identification later without incurring transformation latency, thus supporting multiple hardware configurations while maintaining fast identification speed.
Solution Approach 2:
By performing the computationally intensive transformation operation beforehand and storing the results, the system eliminates transformation-related delays during actual identification operations. This approach allows the system to support multiple hardware configurations versatilely while maintaining low identification latency, as the transformation work has already been completed during enrollment.
Data Source
AI summary
A biometric identification system processes input data acquired by input devices to determine embeddings used to identify a user. Different types of input devices or hardware configurations of input devices may produce different output. Each hardware configuration may be associated with respective representation data. A set of transformer networks are used to transform an embedding from one representation data associated with a first type of device or hardware configuration to another. This enables user participation via different configurations of hardware without requiring users to re-enroll for different input devices or hardware configurations. Opportunistic updates are made to the embeddings as embeddings native to a particular configuration of hardware are acquired from the user.