EMPATH: face, emotion, and gender recognition using holons
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
What does the retina know about natural scenes?
Neural Computation
Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coding, Analysis, Interpretation, and Recognition of Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic recognition of facial expressions using hidden markov models and estimation of expression intensity
Semisupervised learning of classifiers with application to human-computer interaction
Semisupervised learning of classifiers with application to human-computer interaction
Journal of Cognitive Neuroscience
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A new approach for recognizing facial expressions in various internal states that is illumination-invariant and without detectable cues such as a neutral expression is proposed. First, we propose a zero-phase whitening step of the images for illumination-invariant. Second, we developed a representation of face images based on principal component analysis(PCA) representation excluded the first 1 principle component as the features for facial expression recognition, regardless of neutral expression. The PCA basis vectors for this data set had reflected well the changes in facial expression. Finally, a neural network model for classification of facial expressions based on dimension model was created. The dimensional model recognizes not only six facial expressions related to six basic emotions (happiness, sadness, surprise, angry, fear, disgust), but also expressions of various internal states. PCA representations excluded the first 1 principle component and neural network model on the two-dimensional structure of emotion have improved the limitation of expression recognition based on a small number of discrete categories of emotional expressions, and have overcome the problems of lighting sensitivity and dependence on cues such as a neutral expression.