Orthogonal Nonnegative CP Factorization for Image Representation and Recognition
Kun He · Dianzi Ke-ji Daxue xuebao · 2011
An orthogonal non-negative CANDECOMP/PARAFAC factorization algorithm(ONNCP) is proposed.With the orthogonal constrain,the low-dimensional presentations of samples are kept non-negative in ONNCP.The relationship between NNCP and NMF is analyzed theoretically.The solution process and the convergence of the algorithm are discussed.The experiments indicate that,compared with other non-negative factorization algorithms,ONNCP can reduce the redundancy of the base images and enhance the sparseness of the base images due to its orthogonality.It also ensures the low-dimensional feature is non-negative.The algorithm can achieve better recognition rate in facial expression recognition and will convergence a fixed point.Furthermore,the algorithm can be generalized to any order tensor.