Application-Specific Biometric Gallery Segmentation for Faster Identification
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Solution Overview
Problem
Existing biometric identification systems face challenges in efficiently processing large biometric galleries, leading to increased time and resource usage for identification tasks.
Innovation Solution
The implementation of an intelligent biometric gallery management system that creates application-specific galleries by pulling relevant biometric information for subsets of the population, allowing for more efficient biometric identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a large biometric gallery containing information for a population is used for identification, then the system can identify any person in the population, but the time required for biometric identification increases and device resources are consumed
Solution Approach 1:
The patent segments the large biometric gallery into multiple smaller application-specific galleries based on different criteria such as demographic characteristics, geographic location, or application type. This allows the system to divide the population database into manageable subsets that can be processed more efficiently for specific identification tasks.
Solution Approach 2:
The patent extracts only the relevant subset of biometric information needed for a specific application from the large population gallery. By pulling out only the necessary data for particular applications, the system reduces the amount of data that needs to be processed while maintaining identification capability for the target population.
2Adaptability or versatility
If a large biometric gallery containing information for a population is used for identification, then the system can identify any person in the population, but device resources are consumed
Solution Approach 1:
The patent segments the large biometric gallery into multiple smaller application-specific galleries based on different criteria such as demographic characteristics, geographic location, or application type. This allows the system to divide the population database into manageable subsets that can be processed more efficiently for specific identification tasks.
Solution Approach 2:
The patent extracts only the relevant subset of biometric information needed for a specific application from the large population gallery. By pulling out only the necessary data for particular applications, the system reduces the amount of data that needs to be processed while maintaining identification capability for the target population.
3Reliability
If the entire biometric gallery is processed for every identification task, then comprehensive identification is achieved, but processing efficiency decreases
Solution Approach 1:
The patent applies local quality by creating application-specific galleries tailored to particular identification needs. Each gallery is optimized with the appropriate level of detail and scope for its specific application, rather than using a uniform approach for all identification tasks. This improves processing efficiency while maintaining the reliability needed for each specific application context.
Data Source
AI summary
A system provides intelligent gallery management for biometrics. A first gallery is obtained that includes biometric and/or other information on a population of people. An application is identified. A subset of the population of people is identified based on the application. A second gallery is derived from the first gallery by pulling the information for the subset of the population of people without pulling the information for the population of people not in the subset. Biometric identification (such as facial recognition) for the application may then be performed using the second gallery rather than the first gallery. In this way, the system is improved as less time is required for biometric identification, fewer device resources are used, and so on.