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14

ECCV
2008
Springer

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Discriminative Locality Alignment

13 years 5 months ago

Discriminative Locality Alignment

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—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.

Tianhao Zhang, Dacheng Tao, Jie Yang

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Binary Principal Component | Computer Vision | ECCV 2008 | Nonnegative Matrix Factorization | Subspace Selection Algorithm |

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Added	09 Nov 2010
Updated	09 Nov 2010
Type	Conference
Year	2008
Where	ECCV
Authors	Tianhao Zhang, Dacheng Tao, Jie Yang

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