Dynamic Face Database Update for Identity Verification
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Solution Overview
Problem
Current face verification technologies rely on static face features stored in databases, which may not adapt well to changes in a user's appearance over time or in different scenarios, potentially leading to inaccurate identity verification.
Innovation Solution
A method that compares feature data from a user image with data in a database, determines the similarity, and updates the database based on predetermined thresholds, incorporating additional verification methods like password or fingerprint verification when necessary, to ensure accurate identity verification across varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static face features are stored in a database for verification, then the verification process is simple and fast, but the system cannot adapt to changes in user appearance over time
Solution Approach 1:
The patent implements dynamic database updates by comparing newly captured face features with existing database entries. When the similarity exceeds a predetermined threshold, the database is automatically updated to reflect the user's current appearance, enabling the system to adapt to appearance changes over time while maintaining a relatively simple verification process
Solution Approach 2:
The system employs feedback mechanisms by continuously comparing new face features with database entries and using the comparison results to determine whether database updates are needed. This feedback loop allows the system to self-adjust and adapt to appearance changes without requiring complex manual reconfiguration
2Measurement precision
If multiple verification methods are used to improve accuracy, then identity verification accuracy improves, but the verification process becomes more complex
Solution Approach 1:
The patent applies partial action by implementing a tiered verification approach: first performing simple image verification against the database, and only when the similarity falls below the threshold but above a lower threshold, then prompting for additional verification methods. This ensures high accuracy when needed while keeping the process simple for most cases
Solution Approach 2:
The verification process is segmented into distinct stages: initial image-based verification, threshold evaluation, and conditional alternative verification methods. This segmentation allows the system to achieve high accuracy through multiple methods when necessary while maintaining simplicity for straightforward verification cases
Data Source
AI summary
Embodiments of the present disclosure provide method for processing images and apparatuses, method for identity verifications and apparatuses, electronic devices, and storage media. The method for processing images includes: obtaining first feature data of a first user image; comparing the first feature data with at least one piece of second feature data included in a database to obtain a comparison result; and determining, according to the comparison result, whether to update the database. According to the embodiments of the present disclosure, it is beneficial to the database to adapt to identity verification in different scenarios and changes in user's appearance generated over time, thereby improving the user experience.