The researchers developed a method called weighted multiple kernel Fisher discriminant analysis to improve face feature extraction. By combining different projections obtained from single kernel Fisher discriminant, they were able to extract features and classify faces more accurately. The experimental results showed that this new method is better than using just a single kernel function for facial feature extraction and classification.