A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Affective computing
Automatic Classification of Single Facial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coding Facial Expressions with Gabor Wavelets
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Comprehensive Database for Facial Expression Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Camera models and machine perception
Camera models and machine perception
Learning and example selection for object and pattern detection
Learning and example selection for object and pattern detection
Neural Computation
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face detection with the modified census transform
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Recognizing Human Emotional State From Audiovisual Signals
IEEE Transactions on Multimedia
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This interdisciplinary study proposes a method for architectural design analysis of house façades which is based on face detection and facial expression classification. The hypothesis is that abstract face expression features can occur in the architectural design of house façades and will potentially trigger emotional responses of observers. The approach used statistical learning with support vector machines for classification. In the computer experiments the system was trained using a specifically composed image data base consisting of human faces and smileys. Afterwards it was applied to a series of test images of human facial expressions and house façades. The experiments show how facial expression pattern associated with emotional states such as surprise, fear, happiness, sadness, anger, disgust, contempt or neutral could be recognised in both image data sets.