Vehicle Emotion Recognition Feature Point Update Mechanism
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Solution Overview
Problem
Current vehicle emotion determination technologies using biometrics face challenges in accurately evaluating and updating data structures to improve emotion recognition accuracy, leading to inconsistent results.
Innovation Solution
An apparatus and method that includes a storage system for hierarchical feature points and a contribution list, where a controller compares and updates feature points based on matching or non-matching results, replacing points when necessary and evaluating accuracy to determine the driver's emotion using biometric information from sensors like cameras and microphones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the data structure is updated by replacing feature points based on contribution rank, then the accuracy of emotion determination is improved, but the complexity of the system increases
Solution Approach 1:
The system pre-establishes a contribution list that ranks feature points by their importance to emotion determination before actual emotion analysis begins. This preliminary organization of feature points by contribution rank allows the system to quickly identify and replace the most impactful feature points when updates are needed, improving accuracy without requiring complex real-time analysis of all feature points during emotion determination.
Solution Approach 2:
The data structure is segmented into hierarchical levels with feature points organized by their contribution rank to emotion determination. This segmentation allows the system to selectively update only the most critical feature points (those with higher contribution ranks) rather than requiring comprehensive updates across the entire data structure, thereby improving accuracy while managing system complexity.
2Speed
If biometric information is collected and analyzed in real-time, then the responsiveness of emotion recognition is improved, but the processing time increases
Solution Approach 1:
The system pre-processes and organizes biometric data into a structured format with feature points ranked by contribution before real-time emotion analysis begins. This preliminary organization allows the controller to quickly access and evaluate only the most relevant feature points during real-time operation, improving responsiveness while minimizing the processing time required for actual emotion determination.
Solution Approach 2:
Instead of processing all biometric data points equally, the system focuses on processing only the top-ranked feature points from the contribution list that have the greatest impact on emotion determination. This partial processing approach achieves accurate real-time emotion recognition by concentrating computational resources on the most critical data points rather than uniformly processing the entire dataset.
Data Source
AI summary
An apparatus includes: a storage configured to store a data structure including first one or more feature points hierarchically listed and a contribution list including information about a contribution rank of each of second one or more feature points; and a controller configured to compare the first one or more feature points in the data structure with the second one or more feature points of the contribution list, and to determine whether to update the data structure based on a comparison result.