Driver Emotion Estimation Using Temporal Facial and Physical Data
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Solution Overview
Problem
Conventional emotion estimation devices cannot accurately estimate driver emotions due to the duration aspect, as they rely solely on the degree of awakening and comfort, failing to consider temporal changes.
Innovation Solution
An emotion estimation device that processes facial and physical information to estimate driving capability and facial expressions, then represents emotions by degree of comfort and activeness based on temporal changes in these factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If emotions are estimated only by degree of awakening and degree of comfort, then the estimation process is simple, but the emotion estimation accuracy deteriorates due to inability to consider temporal changes
Solution Approach 1:
The system performs preliminary detection of facial information and physical information, then uses this data to estimate driving capability and facial expressions over time. This preliminary action allows the system to build a temporal foundation for more accurate emotion estimation without adding complex real-time processing
Solution Approach 2:
The system transitions from static emotion estimation (based only on current awakening and comfort levels) to dynamic emotion estimation by incorporating temporal changes in driving capability and facial expressions. This dynamic approach captures the evolving nature of emotions while maintaining manageable system complexity
2Measurement precision
If temporal changes are considered in emotion estimation, then emotion estimation accuracy improves, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The emotion estimation process is segmented into distinct functional modules: facial information detection, physical information detection, driving capability estimation, facial expression estimation, and final emotion estimation. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while improving accuracy
Solution Approach 2:
The processing circuitry is designed to perform multiple functions: detecting facial information, detecting physical information, estimating driving capability, estimating facial expressions, and estimating emotions. This multi-functionality reduces the need for separate dedicated components for each function, thereby managing device complexity while achieving accurate temporal-based emotion estimation
Data Source
AI summary
A facial information detecting unit detects facial information related to facial features of a driver of a vehicle. A physical information detecting unit detects physical information related to physical features of the driver. A driving capability estimating unit estimates a driving capability of the driver on the basis of the facial information and the physical information. A facial expression estimating unit estimates the facial expression of the driver on the basis of the facial information. An emotion estimating unit estimates the emotion of the driver represented by the degree of comfort and the degree of activeness on the basis of temporal changes in the driving capability of the driver and the facial expression of the driver.