Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition

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 proposed system uses the distances of LCGBP histograms between neutral faces and AU containing faces combined with an AU-specific feature selection and classification process. We achieve 98.6% overall accuracy in our tests with the extended Cohn-Kanade database, which is higher than achieved previously by any state-of-the-art method.


Editor(s):
Salah, Aa
Hung, H.
Aran, O.
Gunes, H.
Published in:
Human Behavior Understanding (Hbu 2013), 8212, 136-147
Presented at:
4th International Workshop on Human Behavior Understanding (HBU)
Year:
2013
Publisher:
Berlin, Springer-Verlag Berlin
ISSN:
0302-9743
ISBN:
978-3-319-02714-2978-3-319-02713-5
Laboratories:




 Record created 2014-02-17, last modified 2018-09-13


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