ML Anthology

Pairwise Rotation Invariant Co-Occurrence Local Binary Pattern

Xianbiao Qi, Rong Xiao, Jun Guo, Lei Zhang
ECCV 2012 pp. 158-171
doi:10.1007/978-3-642-33783-3_12 /eccv/2012/qi2012eccv-pairwise/

Abstract

In this work, we introduce a novel pairwise rotation invariant co-occurrence local binary pattern (PRI-CoLBP) feature which incorporates two types of context - spatial co-occurrence and orientation co-occurrence. Different from traditional rotation invariant local features, pairwise rotation invariant co-occurrence features preserve relative angle between the orientations of individual features. The relative angle depicts the local curvature information, which is discriminative and rotation invariant. Experimental results on the CUReT, Brodatz, KTH-TIPS texture dataset, Flickr Material dataset, and Oxford 102 Flower dataset further demonstrate the superior performance of the proposed feature on texture classification, material recognition and flower recognition tasks.

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Cite

Text

Qi et al. "Pairwise Rotation Invariant Co-Occurrence Local Binary Pattern." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33783-3_12

Markdown

[Qi et al. "Pairwise Rotation Invariant Co-Occurrence Local Binary Pattern." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/qi2012eccv-pairwise/) doi:10.1007/978-3-642-33783-3_12

BibTeX

@inproceedings{qi2012eccv-pairwise,
  title     = {{Pairwise Rotation Invariant Co-Occurrence Local Binary Pattern}},
  author    = {Qi, Xianbiao and Xiao, Rong and Guo, Jun and Zhang, Lei},
  booktitle = {European Conference on Computer Vision},
  year      = {2012},
  pages     = {158-171},
  doi       = {10.1007/978-3-642-33783-3_12},
  url       = {https://mlanthology.org/eccv/2012/qi2012eccv-pairwise/}
}