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Journal of Electronic Imaging

Feature matching using modified projective nonnegative matrix factorization
Author(s): Weidong Yan; Zheng Tian; Jinhuan Wen; Lulu Pan
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Paper 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.

Paper Details

Date Published: 27 February 2012
PDF: 9 pages
J. Electron. Imaging. 21(1) 013005 doi: 10.1117/1.JEI.21.1.013005
Published in: Journal of Electronic Imaging Volume 21, Issue 1
Show Author Affiliations
Weidong Yan, Northwestern Polytechnical Univ. (China)
Zheng Tian, Northwestern Polytechnical Univ. (China)
Jinhuan Wen, Northwestern Polytechnical Univ. (China)
Lulu Pan, Northwestern Polytechnical Univ. (China)


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