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Feature matching using modified projective nonnegative matrix factorization

[+] Author Affiliations
Weidong Yan

Northwestern Polytechnical University, School of Science, Xi’an 710072, China

Zheng Tian

Northwestern Polytechnical University, School of Science, Xi’an 710072, China

Jinhuan Wen

Northwestern Polytechnical University, School of Science, Xi’an 710072, China

Lulu Pan

Northwestern Polytechnical University, School of Science, Xi’an 710072, China

J. Electron. Imaging. 21(1), 013005 (Feb 27, 2012). doi:10.1117/1.JEI.21.1.013005
History: Received June 30, 2011; Revised December 13, 2011; Accepted January 5, 2012
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Abstract.  We present a novel matching method to find the correspondences among different images containing the same object. In the proposed method, by considering each feature point-set as a matrix, two point-sets are projected onto a common subspace using modified projective nonnegative matrix factorization. The core idea of the proposed approach is to jointly factorize of the two feature matrices and the matching operate on embeddings of the two point-sets in the common subspace. Furthermore, it is robust to noise due to the merit of the subspace method. The proposed approach was tested for matching accuracy, and robustness to noise. Its performance on synthetic and real images was compared with state-of-the-art reference algorithms.

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Topics

Matrices ; Algorithms

Citation

Weidong Yan ; Zheng Tian ; Jinhuan Wen and Lulu Pan
"Feature matching using modified projective nonnegative matrix factorization", J. Electron. Imaging. 21(1), 013005 (Feb 27, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.1.013005


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