Pyramid-Based Multi-scale LBP Features for Face Recognition

To efficiently extract local and global features in face description and recognition, a pyramid-based multi-scale LBP approach is proposed. Firstly, the face image pyramid is constructed through multi-scale analysis. Then the LBP operator is applied to each level of the image pyramid to extract facial features under various scales. Finally, all the extracted features are concatenated into an enhanced feature vector which is used as the face descriptor. Experimental results on ORL and FERET face databases show that the proposed LBP representation is highly efficient with good performance in face recognition and is robust to illumination, facial expression and position variation.