Facial Expression Recognition in Videos using a Novel Multi-Class Support Vector Machines Variant

@article{Kotsia2007FacialER,
  title={Facial Expression Recognition in Videos using a Novel Multi-Class Support Vector Machines Variant},
  author={Irene Kotsia and Nikos Nikolaidis and Ioannis Pitas},
  journal={2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07},
  year={2007},
  volume={2},
  pages={II-585-II-588}
}
In this paper, a novel class of support vector machines (SVM) is introduced to deal with facial expression recognition. The proposed classifier incorporates statistic information about the classes under examination into the classical SVM. The developed system performs facial expression recognition in facial videos. The grid tracking and deformation algorithm used tracks the Candide grid over time as the facial expression evolves, until the frame that corresponds to the greatest facial… CONTINUE READING

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