Title :
Binary Sparse Nonnegative Matrix Factorization
Author :
Yuan, Yuan ; Li, Xuelong ; Pang, Yanwei ; Lu, Xin ; Tao, Dacheng
Author_Institution :
Sch. of Eng. & Appl. Sci., Aston Univ., Birmingham
fDate :
5/1/2009 12:00:00 AM
Abstract :
This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.
Keywords :
computer graphics; image processing; matrix decomposition; sparse matrices; binary principal component analysis; binary sparse nonnegative matrix factorization; face images; fast part-based subspace selection algorithm; image occlusions; Fast algorithms; non-negative matrix factorization; part-based representation; sparseness; subspace selection;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
DOI :
10.1109/TCSVT.2009.2017306
