Natural Gesture Authentication Using Ratio Comparison
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Solution Overview
Problem
Current user authentication systems face high failure rates when using natural gesture-based inputs due to the inherent variability and difficulty in reproducing analog-type inputs, particularly in augmented, virtual, and mixed reality technologies.
Innovation Solution
A user authentication system and method that recognizes natural gesture inputs from image data, allocates weight values to authentication steps, and compares actual and reference ratios to determine authentication success, thereby reducing failure rates and enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural gesture-based input is used for user authentication, then ease of operation is improved, but reliability deteriorates due to high failure rates
Solution Approach 1:
The authentication process is divided into multiple discrete steps, each recognizing a specific natural gesture input. By segmenting the authentication into multiple steps with individual recognition tasks, the system maintains ease of operation while improving overall reliability through cumulative verification
Solution Approach 2:
The system changes the parameter of authentication evaluation from binary (pass/fail) to a multi-dimensional assessment including recognition accuracy, gesture sequence compliance, and confidence scores. This allows natural gestures to be authenticated more reliably while preserving their natural ease of operation
2Reliability
If multiple authentication steps are implemented, then reliability is improved, but device complexity increases
Solution Approach 1:
The gesture recognition module serves multiple functions: it recognizes various natural gestures, determines authentication steps, evaluates recognition results, and makes authentication decisions. By making this single module multi-functional, the system achieves high reliability through multiple authentication steps without proportionally increasing device complexity
3Measurement precision
If weight values are allocated to authentication steps, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Different weight values are assigned to different authentication steps based on their individual importance and reliability characteristics. This local differentiation of quality (weight values) allows precise measurement of authentication confidence without requiring complex overall system changes
Solution Approach 2:
The system applies weight values selectively to authentication steps where they are most needed, rather than uniformly to all steps. This partial application of complexity achieves sufficient measurement precision while avoiding unnecessary device complexity
Data Source
AI summary
Provided is a user authentication method using a natural gesture input. The user authentication method includes recognizing a plurality of natural gesture inputs from image data of a user, determining number of the plurality of natural gesture inputs as total number of authentication steps, determining a reference ratio representing a ratio of number of authentication steps requiring authentication pass to the total number of the authentication steps, determining an actual ratio representing a ratio of number of authentication steps, where authentication has actually passed, to the total number of the authentication steps, and performing authentication on the user, based on a result obtained by comparing the actual ratio and the reference ratio.