Static and dynamic 3D facial expression recognition: A comprehensive survey. Georgia Sandbach, Stefanos Zafeiriou, Maja Pantic, Lijun Yin

Article: Static and dynamic 3D facial expression recognition: A comprehensive survey.

Author: Georgia Sandbach, Stefanos Zafeiriou, Maja Pantic, Lijun Yin
Source: Image and Vision Computing Journal; Volume 30, Issue 10, pp 683–697.
Date: October 2012

Abstract: Automatic facial expression recognition constitutes an active research field due to the latest advances in computing technology that make the user’s experience a clear priority. The majority of work conducted in this area involves 2D imagery, despite the problems this presents due to inherent pose and illumination variations. In order to deal with these problems, 3D and 4D (dynamic 3D) recordings are increasingly used in expression analysis research. In this paper we survey the recent advances in 3D and 4D facial expression recognition. We discuss developments in 3D facial data acquisition and tracking, and present currently available 3D/4D face databases suitable for 3D/4D facial expressions analysis as well as the existing facial expression recognition systems that exploit either 3D or 4D data in detail. Finally, challenges that have to be addressed if 3D facial expression recognition systems are to become a part of future applications are extensively discussed.

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