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Automatic emotion recognition systems based on supervised machine learning require reliable annotation of a↵ective behaviours to build useful models. Whereas the dimensional approach is getting more and more popular for rating a↵ective behaviours in continuous time domains, e. g., arousal and valence, methodologies to take into account reaction lags of the(More)
This article describes a system for participation in the Facial Expression Recognition and Analysis (FERA2015) sub-challenge for spontaneous action unit occurrence detection. The problem of AU detection is a multi-label classification problem by its nature, which is a fact overseen by most existing work. The correlation information between AUs has the(More)
Automatic facial expression analysis promises to be a game-changer in many application areas. But before this promise can be fulfilled, it has to move from the laboratory into the wild. The Emotion Recognition in the Wild challenge provides an opportunity to develop approaches in this direction. We propose a novel Distribution-based Pairwise Iterative(More)
Automatic facial action unit (AU) detection in videos is the key ingredient to all systems that utilize a subject face for either interaction or analysis purposes. With the ever growing range of possible applications, achieving a high accuracy in the simplest possible manner gains even more importance. In this paper, we present new features obtained by(More)
Monitoring the attentive and emotional status of the driver is critical for the safety and comfort of driving. In this work a real-time non-intrusive monitoring system is developed, which detects the emotional states of the driver by analyzing facial expressions. The system considers two negative basic emotions, anger and disgust, as stress related(More)
Curvature Gabor features have recently been shown to be powerful facial texture descriptors with applications on face recognition. In this paper we introduce their use in facial action unit (AU) detection within a novel framework that combines multiple Local Curvature Gabor Binary Patterns (LCGBP) on different filter sizes and curvature degrees. The(More)
GOAL Difficult tracheal intubation is a major cause of anesthesia-related injuries with potential life threatening complications. Detection and anticipation of difficult airway in the preoperative period is, thus, crucial for the patients' safety. We propose an automatic face-analysis approach to detect morphological traits related to difficult intubation(More)
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