摘要
Though manifold learning has been success-fully applied in wide areas, such as data visu-alization, dimension reduction and speech rec-ognition;few researches have been done with the combination of the information theory and the geometrical learning. In this paper, we carry out a bold exploration in this field, raise a new approach on face recognition, the intrinsic α-Rényi entropy of the face image attained from manifold learning is used as the characteristic measure during recognition. The new algorithm is tested on ORL face database, and the ex-periments obtain the satisfying results.
Though manifold learning has been success-fully applied in wide areas, such as data visu-alization, dimension reduction and speech rec-ognition;few researches have been done with the combination of the information theory and the geometrical learning. In this paper, we carry out a bold exploration in this field, raise a new approach on face recognition, the intrinsic α-Rényi entropy of the face image attained from manifold learning is used as the characteristic measure during recognition. The new algorithm is tested on ORL face database, and the ex-periments obtain the satisfying results.
