Person Identification Re-Registration Under Changing Input Environments
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Solution Overview
Problem
Conventional person identification technologies struggle to prevent performance degradation due to changes in the use environment, such as noise or changes in input devices, leading to inaccurate identification.
Innovation Solution
An information processing apparatus that includes an extraction unit to extract personal features, a specifying unit to identify individuals, an environment information acquisition unit to detect changes, and a re-registration unit to update the person dictionary when environmental changes occur or accuracy thresholds are breached, using methods like re-training the personal feature model or superimposing environment information to maintain accurate identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional person identification technology is used, then identification can be performed, but identification performance degrades when use environment changes
Solution Approach 1:
The system dynamically adapts to environmental changes by detecting changes in environment information (such as noise characteristics, lighting conditions, or sensor variations) and automatically re-registering or re-training the personal feature model when changes exceed a threshold. This makes the identification system flexible and adaptive rather than static, resolving the contradiction between maintaining reliable identification and adapting to varying environments.
Solution Approach 2:
The system implements a feedback mechanism where environment information is continuously monitored and compared against reference data. When environmental changes are detected that could affect identification accuracy, the system triggers re-registration or re-training processes to update the personal feature model, thereby maintaining identification performance across different environmental conditions.
2Measurement precision
If person dictionary is re-registered frequently to maintain accuracy, then identification accuracy is maintained, but processing time and system complexity increase
Solution Approach 1:
Instead of continuously re-registering the entire person dictionary, the system performs partial updates only when environmental changes exceed a predetermined threshold. This selective approach maintains identification accuracy while minimizing the time and computational resources required for updates, avoiding unnecessary full re-registrations.
Solution Approach 2:
The system changes the operational parameters of the identification system based on environmental conditions. By monitoring environment information and comparing it against reference data, the system adjusts whether to perform re-registration or re-training operations, optimizing the balance between maintaining accuracy and minimizing processing time through parameter-based decision making.
Data Source
AI summary
Even when use environment changes, degradation of identification performance is prevented. An information processing apparatus according to an embodiment includes one or more input devices, an extraction unit, a specifying unit, an environment-information-acquisition unit, an analysis unit, and a re-registration unit. The input devices acquire input information. The extraction unit extracts a feature-amount indicating a feature of a person from the input information by using a personal-feature model. The specifying unit specifies the person by comparing the feature-amount with a feature-amount indicated by a person dictionary. The environment-information-acquisition unit acquires environment information from the input information. The analysis unit analyzes a change in the environment information and specifying accuracy of the person by the specifying unit. The re-registration unit performs control to re-register the person dictionary when there is a change in the environment information or when the specifying accuracy is less than an accuracy threshold.