Real-Time Emotion Recognition: a Novel Method for Geometrical Facial Features Extraction
Loconsole, C. L.
; Miranda, C.R.
Real-Time Emotion Recognition: a Novel Method for Geometrical Facial Features Extraction, Proc International Conf. on Computer Vision Theory and Applications - VISAPP, Lisbon, Portugal, Vol. 01, pp. 378 - 385, January, 2014.
Digital Object Identifier: 10.5220/0004738903780385
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Facial emotions provide an essential source of information commonly used in human communication. For humans, their recognition is automatic and is done exploiting the real-time variations of facial features. However, the replication of this natural process using computer vision systems is still a challenge, since automation and real-time system requirements are compromised in order to achieve an accurate emotion detection. In this work, we propose and validate a novel methodology for facial features extraction to automatically recognize
facial emotions, achieving an accurate degree of detection. This methodology uses a real-time face tracker output to define and extract two new types of features: eccentricity and linear features. Then, the features are
used to train a machine learning classifier. As result, we obtain a processing pipeline that allows classification of the six basic Ekman’s emotions (plus Contemptuous and Neutral) in real-time, not requiring any manual intervention or prior information of facial traits.