Kernel conditional ordinal random fields for temporal segmentation of facial action units

Authors:
Ognjen Rudovic;Vladimir Pavlovic;Maja Pantic
Affiliations:
Computing Dept., Imperial College London, UK;Dept. of Computer Science, Rutgers University;Computing Dept., Imperial College London, UK,EEMCS, University of Twente, The Netherlands
Venue:
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
Year:
2012

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Abstract

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.