Turkish Journal of Electrical Engineering and Computer Sciences
Installment of a facial expression is associated with contractions and extensions of specific facial muscles. Noting that expression is about changes, we present a model for expression classification based on facial landmarks dynamics. Our model isolates the trajectory of facial fiducial points by wrapping them up in relevant features and discriminating among various alternatives with a machine learning classification system. The used features are geometric and temporal-based and the classification system is represented by a late fusion framework that combines several neural networks with binary responses. The proposed method is robust, being able to handle complex expression classes.
Feature extraction, machine learning, facial expression recognition
BANDRABUR, ALESSANDRA; FLOREA, LAURA; FLOREA, CORNEL; and MANCAS, MATEI
"Late fusion of facial dynamics for automatic expression recognition,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 25:
4, Article 12.
Available at: https://journals.tubitak.gov.tr/elektrik/vol25/iss4/12
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