Solving the face recognition problem using QR factorization
Jianqiang Gao, Liya Fan, Lizhong Xu · 2012
Inspired and motivated by the idea of LDA/QR presented by Ye and Li, in addition, by the idea of WK- DA/QR and WKDA/SVD presented by Gao and Fan. In this paper, we first consider computational complexity and efficacious of algorithm present a PCA/range(Sb) algorithm for dimensionality reduction of data, which transforms firstly the original space by using a basis of range(Sb) and then in the transformed space applies PCA. Considering computationally expensive and time complexity, we further present an improved version of PCA/range(Sb), denot- ed by PCA/range(Sb)-QR, in which QR decomposition is used at the last step of PCA/range(Sb). In addition, we also improve LDA/GSVD, LDA/range(Sb) and PCA by means of QR decomposition. Extensive experiments on face images from UCI data sets show the effectiveness of the proposed algorithms.