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Published in:
2012 | OriginalPaper | Chapter
Kernel Conditional Ordinal Random Fields for Temporal Segmentation of Facial Action Units
Authors : Ognjen Rudovic, Vladimir Pavlovic, Maja Pantic
Published in: Computer Vision – ECCV 2012. Workshops and Demonstrations
Publisher: Springer Berlin Heidelberg
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We consider the problem of automated recognition of temporal segments (neutral, onset, apex and offset) of Facial Action Units. To this end, we propose the Laplacian-regularized Kernel Conditional Ordinal Random Field model. In contrast to standard modeling approaches to recognition of AUs’ temporal segments, which treat each segment as an independent class, the proposed model takes into account
ordinal
relations between the segments. The experimental results evidence the effectiveness of such an approach.