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Recognizing Facial Expressions in Videos Using a Facial Action Analysis-Synthesis Scheme

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2 Author(s)
Dornaika, F. ; Computer Vision Center, Spain ; Raducanu, B.

In this paper, we propose a novel approach for facial expression analysis and recognition. The proposed approach relies on tracked facial actions provided by an appearance-based 3D face tracker. For each universal expression, a dynamical model for facial actions given by an auto-regressive process is learned from training data. We classify a given image in an unseen video into one of the universal facial expression categories using an analysis-synthesis scheme. This scheme uses all models and select the one that provides the most consistent synthesized spatio-temporal facial actions. The dynamical models can be utilized in the tasks of synthesis and prediction. Experiments using unseen videos demonstrated the effectiveness of the developed method.

Published in:

Video and Signal Based Surveillance, 2006. AVSS '06. IEEE International Conference on

Date of Conference:

Nov. 2006

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