Feature matching using modified projective nonnegative matrix factorization

Weidong Yan; Zheng Tian; Jinhuan Wen; Lulu Pan

doi:10.1117/1.JEI.21.1.013005

27 February 2012 Feature matching using modified projective nonnegative matrix factorization

Weidong Yan, Zheng Tian, Jinhuan Wen, Lulu Pan

Author Affiliations +

Journal of Electronic Imaging, Vol. 21, Issue 1, 013005 (February 2012). https://doi.org/10.1117/1.JEI.21.1.013005

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.

Citation Download Citation

Weidong Yan, Zheng Tian, Jinhuan Wen, and Lulu Pan "Feature matching using modified projective nonnegative matrix factorization," Journal of Electronic Imaging 21(1), 013005 (27 February 2012). https://doi.org/10.1117/1.JEI.21.1.013005

Published: 27 February 2012

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