Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition
Details
State: Public
Version: author
Serval ID
serval:BIB_617B1CD800CB
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition
Title of the conference
HBU 2013, International Workshop on Human Behavior Understanding, in conjunction with ACM Multimedia
Publication state
Published
Issued date
2013
Volume
8212
Series
Lecture Notes in Computer Science
Pages
136-147
Language
english
Abstract
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-artmethod.
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-artmethod.
Keywords
Facial action unit detection, Curvature Gabor Wavelets, Local Binary Patterns, Automatic facial expression, analysis
Create date
06/01/2014 21:46
Last modification date
20/08/2019 15:18
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