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The Function of Color and Structure Based on EEG Features in Landscape Recognition
Yuting Wang1,2, Shujian Wang1,2, Ming Xu1,2
1Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China.
Summary
Human brain responses to landscape aesthetics were analyzed using electroencephalography (EEG). Findings show distinct brain wave patterns for color and structure, guiding future landscape design.
Area of Science:
- Neuroscience
- Environmental Psychology
- Human-Computer Interaction
Background:
- Human visual perception relies on both color and structure.
- Landscape quality and aesthetics are influenced by these visual elements.
- Understanding brain responses to landscapes can inform design.
Purpose of the Study:
- To investigate electroencephalography (EEG) signals in response to landscape images.
- To differentiate the impact of color and structure on visual perception.
- To identify optimal classification methods for EEG-based landscape analysis.
Main Methods:
- EEG signals were recorded using liveamp32 equipment.
- Participants viewed landscape images, color-filtered structure images, and structure-filtered color images.
- Support Vector Machine (SVM) classifier was employed for data analysis.
Main Results:
- SVM achieved high accuracy (up to 98.3%) in landscape classification using EEG beta waves.
- Color and structure significantly influenced alpha and gamma wave responses, respectively.
- Specific brain wave patterns (alpha, beta, gamma) showed significant differences across landscape types and scenarios.
Conclusions:
- Color and structure are critical components influencing human perception of landscapes.
- EEG analysis, particularly with SVM, is effective for classifying landscape features.
- Findings offer valuable insights for landscape design and planning, emphasizing balanced use of color and structure.
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