A novel phase congruency based descriptor for dynamic facial expression analysis
Teoh, Eam Khwang
Date of Issue2014-07-01
School of Electrical and Electronic Engineering
Representation and classification of dynamic visual events in videos have been an active field of research. This work proposed a novel spatio-temporal descriptor based on phase congruency concept and applied it to recognize facial expression from video sequences. The proposed descriptor comprises histograms of dominant phase congruency over multiple 3D orientations to describe both spatial and temporal information of a dynamic event. The advantages of our proposed approach are local and dynamic processing, high accuracy, robustness to image scale variation, and illumination changes. We validated the performance of our proposed approach using the Cohn-Kanade (CK+) database where we achieved 95.44% accuracy in detecting six basic emotions. The approach was also shown to increase classification rates over the baseline results for the AVEC 2011 video subchallenge in detecting four emotion dimensions. We also validated its robustness to illumination and scale variation using our own collected dataset.
Phase congruency; Spatio-temporal descriptor; Emotion recognition; Facial expression
Pattern Recognition Letters
© 2014 Elsevier B.V. This is the author created version of a work that has been peer reviewed and accepted for publication by Pattern Recognition Letters, Elsevier B.V. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.patrec.2014.06.009].