Finding Correspondence from Multiple Images via Sparse and Low-Rank Decomposition

  title={Finding Correspondence from Multiple Images via Sparse and Low-Rank Decomposition},
  author={Zinan Zeng and Tsung-Han Chan and Kui Jia and Dong Xu},
We investigate the problem of finding the correspondence from multiple images, which is a challenging combinatorial problem. In this work, we propose a robust solution by exploiting the priors that the rank of the ordered patterns from a set of linearly correlated images should be lower than that of the disordered patterns, and the errors among the reordered patterns are sparse. This problem is equivalent to find a set of optimal partial permutation matrices for the disordered patterns such… CONTINUE READING
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