Curvelet-based Manifold Learning for Face Recognition
Chunli Xia · Guangdian gongcheng · 2010
Curvelet is a multiscale and multidirectional image transformation tool,which can efficiently overcome the redundancy of wavelet in expressing the singular feature along curves of the image,and can obtain a sparse feature representation.Moreover,based on the consideration that high-dimensional image may exist in lower dimensional manifolds,manifold learning is performed on the Curvelet features so as to find low-dimensional structures,which is used for face recognition.Experiments show that the Curvelet features further processed by LLE show better clustering ability than the LLE.Compared with the already existing Gabor-based manifold learning,Curvelet-based manifold learning perform better under both facial expression and illumination changes,and either case sees valuable improvements.Experiments in the Essex expression and Yale B lighting face databases prove this point.