Patchmatch-based automatic lattice detection for near-regular textures

Siying Liu, Tian Tsong Ng, Kalyan Sunkavalli, Minh N. Do, Eli Shechtman, Nathan Carr

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, we investigate the problem of automatically inferring the lattice structure of near-regular textures (NRT) in real-world images. Our technique leverages the PatchMatch algorithm for finding k-nearest-neighbor (kNN) correspondences in an image. We use these kNNs to recover an initial estimate of the 2D wallpaper basis vectors, and seed vertices of the texture lattice. We iteratively expand this lattice by solving an MRF optimization problem. We show that we can discretize the space of good solutions for the MRF using the kNNs, allowing us to efficiently and accurately optimize the MRF energy function using the Particle Belief Propagation algorithm. We demonstrate our technique on a benchmark NRT dataset containing a wide range of images with geometric and photometric variations, and show that our method clearly outperforms the state of the art in terms of both texel detection rate and texel localization score.

Original languageEnglish (US)
Title of host publication2015 International Conference on Computer Vision, ICCV 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages181-189
Number of pages9
ISBN (Electronic)9781467383912
DOIs
StatePublished - Feb 17 2015
Event15th IEEE International Conference on Computer Vision, ICCV 2015 - Santiago, Chile
Duration: Dec 11 2015Dec 18 2015

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2015 International Conference on Computer Vision, ICCV 2015
ISSN (Print)1550-5499

Other

Other15th IEEE International Conference on Computer Vision, ICCV 2015
CountryChile
CitySantiago
Period12/11/1512/18/15

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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  • Cite this

    Liu, S., Ng, T. T., Sunkavalli, K., Do, M. N., Shechtman, E., & Carr, N. (2015). Patchmatch-based automatic lattice detection for near-regular textures. In 2015 International Conference on Computer Vision, ICCV 2015 (pp. 181-189). [7410386] (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2015 International Conference on Computer Vision, ICCV 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCV.2015.29