Emotion-Aware Image Display for Concentration Recovery
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Solution Overview
Problem
Changes in human emotions can lead to reduced concentration, potentially causing accidents or decreased work efficiency, especially in tasks like driving, due to the inability to control emotions effectively when faced with significant stimuli.
Innovation Solution
A method and device that detect facial features, particularly around the eyes, to estimate emotions and adjust the environment, such as displaying calming images or sounds, to help the user regain focus and manage their emotions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If facial expression recognition is applied to detect emotions, then concentration reduction can be inhibited, but device complexity increases
Solution Approach 1:
The system segments facial recognition into specific regions (eyes, eyebrows, mouth) and focuses on detecting changes in these specific areas rather than analyzing the entire face. This reduces computational complexity while maintaining emotion detection accuracy for concentration monitoring purposes.
Solution Approach 2:
The system performs preliminary detection of facial feature points and pre-processes image data to identify regions of interest before full emotion analysis. This preliminary action filters out unnecessary processing and reduces overall system complexity while maintaining reliability in detecting concentration-related emotions.
2Reliability
If real-time emotion detection is implemented, then concentration reduction can be addressed promptly, but processing time increases
Solution Approach 1:
The system applies different processing quality levels to different facial regions. High-resolution analysis is applied only to critical areas like eyes and eyebrows where subtle emotion changes occur, while other areas receive minimal processing. This maintains detection accuracy for concentration-related emotions while reducing overall processing time.
Solution Approach 2:
The system performs partial emotion detection by focusing only on the most informative facial features rather than analyzing all facial expressions equally. This partial action approach detects sufficient emotion information for concentration monitoring without the computational overhead of complete facial analysis, thus reducing processing time.
Data Source
AI summary
A reduction in concentration due to a change in an emotion is inhibited. A change in an emotion of the human is suitably reduced. Part (in particular, an eye or an eye and its vicinity) or the whole of a user's face is detected, a feature of the user's face is extracted from data on the detected part or whole of the face, and an emotion of the user is estimated from the extracted feature of the face. In the case where the estimated emotion is an emotion that might reduce concentration, for example, a stimulus is applied to the sense of sight, the sense of hearing, the sense of touch, the sense of smell, or the like of the user to recover the concentration of the user.