Fast and Scalable Approximate Spectral Matching for Higher Order Graph Matching

@article{Park2014FastAS,
  title={Fast and Scalable Approximate Spectral Matching for Higher Order Graph Matching},
  author={Soonyong Park and Sung-Kee Park and Martial Hebert},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2014},
  volume={36},
  pages={479-492}
}
This paper presents a fast and efficient computational approach to higher order spectral graph matching. Exploiting the redundancy in a tensor representing the affinity between feature points, we approximate the affinity tensor with the linear combination of Kronecker products between bases and index tensors. The bases and index tensors are highly compressed representations of the approximated affinity tensor, requiring much smaller memory than in previous methods, which store the full affinity… CONTINUE READING
Highly Cited
This paper has 25 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 1 time over the past 90 days. VIEW TWEETS

Citations

Publications citing this paper.
Showing 1-10 of 12 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 36 references

A relationship between arbitrary positive matrices and doubly stochastic matrices

  • R. Sinkhorn
  • The Annals of Mathematical Statistics, vol. 35…
  • 1964
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…