Face ID Authentication with Provisional Data Evaluation
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Solution Overview
Problem
Existing information processing systems that utilize shot images for user authentication face challenges in maintaining accuracy and stability, especially when the shooting environment changes, leading to user inconvenience and potential errors in login processes.
Innovation Solution
An information processing device and method that includes an image acquirer, a face authentication section, and a face identification data registration section, which acquires and authenticates user images, updates face identification data, and temporarily holds provisional data for evaluation at predetermined timings, ensuring stable authentication by adjusting shooting conditions to match registered data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If face identification data is updated frequently to improve authentication accuracy, then authentication reliability is improved, but system complexity and processing time increase
Solution Approach 1:
The system performs preliminary evaluation of shot images against registration conditions before proceeding with full authentication processing. By pre-screening images based on shooting conditions (lighting, angle, quality), the system avoids unnecessary complex processing of unsuitable images, thus maintaining high authentication accuracy while reducing overall system complexity
Solution Approach 2:
The authentication process is divided into distinct stages: shot image acquisition, registration condition evaluation, face image extraction, and authentication comparison. This segmentation allows each module to be optimized independently, improving reliability without proportionally increasing overall system complexity
2Reliability
If strict registration conditions are applied to ensure data quality, then authentication reliability is improved, but user burden and processing time increase
Solution Approach 1:
The system automatically evaluates shot images against predefined registration conditions without requiring user intervention. The evaluation of shooting conditions (lighting adequacy, face angle, image quality) and automatic rejection or acceptance of images occurs without user burden, while still ensuring high data quality for reliable authentication
Solution Approach 2:
Registration conditions are established in advance based on optimal shooting parameters. The system pre-evaluates whether shot images meet these conditions before proceeding, automatically guiding users through necessary adjustments without imposing manual evaluation burdens, thus maintaining reliability while easing operation
3Measurement precision
If multiple shot images are evaluated and stored for future reference, then authentication accuracy is improved, but data storage requirements and processing complexity increase
Solution Approach 1:
Instead of uniformly storing all shot images, the system applies quality-based selection where only images meeting specific registration conditions (optimal lighting, angle, clarity) are stored as valid face identification data. This local quality approach ensures high authentication accuracy while minimizing storage requirements by excluding substandard images
Solution Approach 2:
The system performs preliminary quality assessment of shot images against registration conditions before storage. By pre-filtering images based on shooting condition evaluation, the system stores only high-quality data necessary for accurate authentication, avoiding unnecessary storage of low-quality images that would increase data volume without improving accuracy
4Ease of operation
If automatic face image extraction is performed to reduce user burden, then ease of operation is improved, but risk of erroneous authentication increases
Solution Approach 1:
The system automatically extracts face images and performs authentication, then provides feedback on the authentication result to the user. This feedback mechanism allows the system to learn from outcomes and adjust extraction parameters, maintaining ease of operation while improving reliability through iterative optimization based on actual authentication performance
Solution Approach 2:
The system performs preliminary evaluation of shot images against registration conditions before automatic face extraction. By pre-validating that images meet quality standards (proper lighting, angle, clarity), the system reduces the risk of erroneous authentication while maintaining automatic operation, thus improving reliability without increasing user burden
Data Source
AI summary
An information processing device includes: an image acquirer acquiring a shot image of a user; a registered user information holder holding face identification data of a registered user; a face authentication carrying out authentication of a face image in the shot image by using the face identification data held in the registered user information holder; an information processing section executing information processing on a basis of an authentication result by the face authentication section; a face identification data registration section updating the face identification data on a basis of a face image extracted from the shot image; and a provisionally-registered data holder temporarily holding data relating to the face image when the face image satisfies a predetermined condition. The face identification data registration section determines whether or not to update the face identification data on the basis of the face image by evaluating the data.