Regression-based Multi-View Facial Expression Recognition

Rudovic, Ognjen and Patras, Ioannis and Pantic, Maja (2010) Regression-based Multi-View Facial Expression Recognition. In: 20th International Conference on Pattern Recognition, ICPR 2010, 23-26 August 2010, Istanbul, Turkey.

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Abstract:	We present a regression-based scheme for multi-view facial expression recognition based on 2-D geometric features. We address the problem by mapping facial points (e.g. mouth corners) from non-frontal to frontal view where further recognition of the expressions can be performed using a state-of-the-art facial expression recognition method. To learn the mapping functions we investigate four regression models: Linear Regression (LR), Support Vector Regression (SVR), Relevance Vector Regression (RVR) and Gaussian Process Regression (GPR). Our extensive experiments on the CMU Multi-PIE facial expression database show that the proposed scheme outperforms view-specific classifiers by utilizing considerably less training data.
Item Type:	Conference or Workshop Item
Copyright:	© 2011 IEEE
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Human Media Interaction (HMI)
Link to this item:	http://purl.utwente.nl/publications/75896
Official URL:	http://dx.doi.org/10.1109/ICPR.2010.1001
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