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 (pp. pp. 4121-4124).

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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
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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