Sub-pattern locality preserving projection for face recognition
子模式局部保持映射人脸识别

Researches show that sub-pattern based face recognition approaches perform better than whole image based methods in local face information preservation. As manifold learning technologies preserve local manifold structure of the nonlinear sub-manifold while implementing dimension reduction, this paper put forward a sub-pattern locality preserving projection BspLPP. Unlike previous approaches partitioned all training images of different classes into sub-images and used the same location images to form a sub-pattern, BspLPP first partitioned the same class images into different sub-images, used the same location sub-images to form a sub-pattern, and then applied LPP to learn the manifold structure of each sub-pattern. Experimental results show that BspLPP preserves the manifold and local information well and improves the recognition performance.