Facial expression recognition based on improved local binary pattern and class-regularized locality preserving projection
The es-LBP, the es-LBP-s, and cr-LPP are proposed for facial expression recognition. The es-LBP computes the local LBP histograms around some particular fiducial points. To further include the spatial information, symmetric extension is also applied. Cr-LPP can enhance the connection between facial features and expressions. Simulations show that the proposed algorithm achieves the highest recognition rate.
facial expression class-regularized locality preserving projection expression-specific local binary pattern dimensionality reduction feature extraction